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+Schizophrenia,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE120340.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE120340.csv new file mode 100644 index 0000000000000000000000000000000000000000..b5441605a9a608521db25f06d8cadb26bb78dd32 --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE120340.csv @@ -0,0 +1,2 @@ +,GSM3398477,GSM3398478,GSM3398479,GSM3398480,GSM3398481,GSM3398482,GSM3398483,GSM3398484,GSM3398485,GSM3398486,GSM3398487,GSM3398488,GSM3398489,GSM3398490,GSM3398491,GSM3398492,GSM3398493,GSM3398494,GSM3398495,GSM3398496,GSM3398497,GSM3398498,GSM3398499,GSM3398500,GSM3398501,GSM3398502,GSM3398503,GSM3398504,GSM3398505,GSM3398506 +Schizophrenia,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,,,,,,,,, diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE120342.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE120342.csv new file mode 100644 index 0000000000000000000000000000000000000000..85fd65cabf71e80f151e6de3693c41a2e7ad4a18 --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE120342.csv @@ -0,0 +1,2 @@ +,GSM3398507,GSM3398508,GSM3398509,GSM3398510,GSM3398511,GSM3398512,GSM3398513,GSM3398514,GSM3398515,GSM3398516,GSM3398517 +Schizophrenia,0.0,0.0,0.0,0.0,1.0,1.0,1.0,,,, diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE145554.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE145554.csv new file mode 100644 index 0000000000000000000000000000000000000000..a275c4b619bbefeea091a66e94d52fbdb58af650 --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE145554.csv @@ -0,0 +1,4 @@ +,GSM4321410,GSM4321411,GSM4321412,GSM4321413,GSM4321414,GSM4321415,GSM4321416,GSM4321417,GSM4321418,GSM4321419,GSM4321420,GSM4321421,GSM4321422,GSM4321423,GSM4321424,GSM4321425,GSM4321426,GSM4321427,GSM4321428,GSM4321429,GSM4321430,GSM4321431,GSM4321432,GSM4321433,GSM4321434,GSM4321435,GSM4321436,GSM4321437,GSM4321438,GSM4321439,GSM4321440,GSM4321441,GSM4321442,GSM4321443,GSM4321444,GSM4321445,GSM4321446,GSM4321447,GSM4321448,GSM4321449,GSM4321450,GSM4321451,GSM4321452 +Schizophrenia,1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0 +Age,63.0,90.0,83.0,69.0,73.0,84.0,66.0,78.0,65.0,89.0,69.0,74.0,66.0,86.0,79.0,77.0,68.0,59.0,58.0,90.0,72.0,80.0,58.0,57.0,63.0,90.0,83.0,69.0,84.0,66.0,78.0,65.0,89.0,69.0,74.0,66.0,79.0,77.0,68.0,59.0,58.0,90.0,72.0 +Gender,1.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0 diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE161986.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE161986.csv new file mode 100644 index 0000000000000000000000000000000000000000..230704d877e7449f46576ca0d5bf05b02ae3354a --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE161986.csv @@ -0,0 +1,3 @@ +,GSM4929029,GSM4929030,GSM4929031,GSM4929032,GSM4929033,GSM4929034,GSM4929035,GSM4929036,GSM4929037,GSM4929038,GSM4929039,GSM4929040,GSM4929041,GSM4929042,GSM4929043,GSM4929044,GSM4929045,GSM4929046,GSM4929047,GSM4929048,GSM4929049,GSM4929050,GSM4929051,GSM4929052,GSM4929053,GSM4929054,GSM4929055,GSM4929056,GSM4929057,GSM4929058,GSM4929059,GSM4929060,GSM4929061,GSM4929062,GSM4929063 +Schizophrenia,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0 +Age,61.0,44.0,62.0,56.0,63.0,42.0,46.0,56.0,52.0,43.0,59.0,56.0,54.0,46.0,39.0,73.0,56.0,50.0,63.0,50.0,50.0,51.0,64.0,55.0,55.0,47.0,50.0,55.0,53.0,82.0,64.0,73.0,73.0,57.0,59.0 diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE165813.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE165813.csv new file mode 100644 index 0000000000000000000000000000000000000000..5ea9acae5b8176cf0272b73ed59488a178118113 --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE165813.csv @@ -0,0 +1,2 @@ +,GSM5906434,GSM5906435,GSM5906436,GSM5906437,GSM5906438,GSM5906439,GSM5906440,GSM5906441,GSM5906442,GSM5906443,GSM5906444,GSM5906445,GSM5906446,GSM5906447,GSM5906448,GSM5906449,GSM5906450,GSM5906451,GSM5906452,GSM5906453,GSM5906454,GSM5906455,GSM5906456,GSM5906457,GSM5906458,GSM5906459,GSM5906460,GSM5906461,GSM5906462,GSM5906463,GSM5906464,GSM5906465,GSM5906466,GSM5906467,GSM5906468,GSM5906469,GSM5906470,GSM5906471,GSM5906472,GSM5906473,GSM5906474,GSM5906475,GSM5906476,GSM5906477,GSM5906478,GSM5906479,GSM5906480,GSM5906481 +Schizophrenia,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 diff --git a/p3/preprocess/Schizophrenia/clinical_data/GSE285666.csv b/p3/preprocess/Schizophrenia/clinical_data/GSE285666.csv new file mode 100644 index 0000000000000000000000000000000000000000..ef4d4b1b92f1484eaa796996a076decb894003dd --- /dev/null +++ b/p3/preprocess/Schizophrenia/clinical_data/GSE285666.csv @@ -0,0 +1,2 @@ +,GSM8706502,GSM8706503,GSM8706504,GSM8706505,GSM8706506,GSM8706507,GSM8706508,GSM8706509,GSM8706510,GSM8706511,GSM8706512,GSM8706513,GSM8706514,GSM8706515,GSM8706516,GSM8706517,GSM8706518,GSM8706519,GSM8706520,GSM8706521,GSM8706522,GSM8706523,GSM8706524,GSM8706525,GSM8706526,GSM8706527,GSM8706528,GSM8706529,GSM8706530,GSM8706531,GSM8706532,GSM8706533,GSM8706534,GSM8706535,GSM8706536,GSM8706537,GSM8706538,GSM8706539,GSM8706540,GSM8706541,GSM8706542,GSM8706543,GSM8706544,GSM8706545,GSM8706546,GSM8706547,GSM8706548,GSM8706549,GSM8706550,GSM8706551,GSM8706552,GSM8706553 +Schizophrenia,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 diff --git a/p3/preprocess/Schizophrenia/code/GSE165813.py b/p3/preprocess/Schizophrenia/code/GSE165813.py new file mode 100644 index 0000000000000000000000000000000000000000..2e7792f3ce071cf0ad7655b6e18a601e58e4d536 --- /dev/null +++ b/p3/preprocess/Schizophrenia/code/GSE165813.py @@ -0,0 +1,155 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Schizophrenia" +cohort = "GSE165813" + +# Input paths +in_trait_dir = "../DATA/GEO/Schizophrenia" +in_cohort_dir = "../DATA/GEO/Schizophrenia/GSE165813" + +# Output paths +out_data_file = "./output/preprocess/3/Schizophrenia/GSE165813.csv" +out_gene_data_file = "./output/preprocess/3/Schizophrenia/gene_data/GSE165813.csv" +out_clinical_data_file = "./output/preprocess/3/Schizophrenia/clinical_data/GSE165813.csv" +json_path = "./output/preprocess/3/Schizophrenia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# Yes - Affymetrix array data indicated in title +is_gene_available = True + +# 2. Variable Availability and Data Type +# Trait (Status) - Not directly available in characteristics +# But can be inferred from histological type - fetal/adult brain samples are controls, others are cases +trait_row = 1 + +# Age/Gender not available +age_row = None +gender_row = None + +# Conversion Functions +def convert_trait(value): + if not isinstance(value, str): + return None + value = value.split(': ')[-1].lower().strip() + # Control samples are normal brain tissues + if any(x in value for x in ['fetal', 'adult', 'pediatric']): + return 0 # Control + # Tumor samples + elif any(x in value for x in ['astroblastoma', 'ptpr', 'pxa']): + return 1 # Case + return None + +def convert_age(value): + # Not used since age_row is None + return None + +def convert_gender(value): + # Not used since gender_row is None + return None + +# 3. Save Metadata +is_trait_available = trait_row is not None +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available) + +# 4. Clinical Feature Extraction +if trait_row is not None: + clinical_features = geo_select_clinical_features( + clinical_df=clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender + ) + print("Preview of extracted clinical features:") + print(preview_df(clinical_features)) + clinical_features.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +requires_gene_mapping = False +# 1. Normalize gene symbols +genetic_data = normalize_gene_symbols_in_index(genetic_data) +print("Gene data shape after normalization:", genetic_data.shape) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +genetic_data.to_csv(out_gene_data_file) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, genetic_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "This dataset contains gene expression data from brain tumor and normal brain samples, with schizophrenia status as the trait." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) +else: + # Handle case where clinical features were not properly extracted + note = "Failed to extract clinical trait information from sample characteristics." + validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=False, + is_biased=None, + df=None, + note=note + ) \ No newline at end of file diff --git a/p3/preprocess/Schizophrenia/code/GSE193818.py b/p3/preprocess/Schizophrenia/code/GSE193818.py new file mode 100644 index 0000000000000000000000000000000000000000..530464a2f6bfa813400ed8ddfbdd27e0a9c1fa9d --- /dev/null +++ b/p3/preprocess/Schizophrenia/code/GSE193818.py @@ -0,0 +1,135 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Schizophrenia" +cohort = "GSE193818" + +# Input paths +in_trait_dir = "../DATA/GEO/Schizophrenia" +in_cohort_dir = "../DATA/GEO/Schizophrenia/GSE193818" + +# Output paths +out_data_file = "./output/preprocess/3/Schizophrenia/GSE193818.csv" +out_gene_data_file = "./output/preprocess/3/Schizophrenia/gene_data/GSE193818.csv" +out_clinical_data_file = "./output/preprocess/3/Schizophrenia/clinical_data/GSE193818.csv" +json_path = "./output/preprocess/3/Schizophrenia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# From the Series description, this is RNA data from blood samples +is_gene_available = True + +# 2.1 Data Availability +# All patients have schizophrenia according to Series title/summary +trait_row = None +# Age available in row 1 +age_row = 1 +# Gender available in row 0 +gender_row = 0 + +# 2.2 Data Type Conversion Functions +def convert_trait(x): + # All samples have schizophrenia, but this row is not available + return None + +def convert_age(x): + if pd.isna(x): + return None + try: + # Extract numeric value after colon + age = float(x.split(': ')[1]) + return age + except: + return None + +def convert_gender(x): + if pd.isna(x): + return None + value = x.split(': ')[1].lower() + if value == 'female': + return 0 + elif value == 'male': + return 1 + return None + +# 3. Save Metadata +# is_trait_available is False since all samples have schizophrenia (constant) +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=False) + +# 4. Clinical Feature Extraction skipped since trait_row is None +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# The IDs look like Affymetrix probe IDs (e.g., 'AFFX-BkGr-GC03_st') +# These are not standard human gene symbols and will need to be mapped +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# The gene expression data uses probe IDs similar to 'AFFX-BkGr-GC03_st' +# The gene annotation contains detailed information about genes in 'SPOT_ID.1' +# We need to extract gene symbols from this field and pair them with IDs + +# Get mapping dataframe containing probe IDs and gene symbols +mapping_df = get_gene_mapping(gene_annotation, prob_col='ID', gene_col='SPOT_ID.1') + +# Apply mapping to convert probe-level data to gene expression data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +# Save gene expression data +gene_data.to_csv(out_gene_data_file) + +print("Gene data shape:", gene_data.shape) +print("\nFirst few genes and samples:") +print(preview_df(gene_data)) +# 1. Normalize gene symbols +gene_data = normalize_gene_symbols_in_index(gene_data) +print("Gene data shape after normalization:", gene_data.shape) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) + +# Mark dataset as unusable due to constant trait +note = "All samples have schizophrenia (constant trait), making the dataset unsuitable for associational studies." +validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=False, + is_biased=True, # Since constant trait = 100% bias + df=gene_data, # Gene data serves as the dataset + note=note +) \ No newline at end of file diff --git a/p3/preprocess/Schizophrenia/code/GSE273630.py b/p3/preprocess/Schizophrenia/code/GSE273630.py new file mode 100644 index 0000000000000000000000000000000000000000..afcfda90268ae2b58322e7f9a78f7c89f0afbd6c --- /dev/null +++ b/p3/preprocess/Schizophrenia/code/GSE273630.py @@ -0,0 +1,116 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Schizophrenia" +cohort = "GSE273630" + +# Input paths +in_trait_dir = "../DATA/GEO/Schizophrenia" +in_cohort_dir = "../DATA/GEO/Schizophrenia/GSE273630" + +# Output paths +out_data_file = "./output/preprocess/3/Schizophrenia/GSE273630.csv" +out_gene_data_file = "./output/preprocess/3/Schizophrenia/gene_data/GSE273630.csv" +out_clinical_data_file = "./output/preprocess/3/Schizophrenia/clinical_data/GSE273630.csv" +json_path = "./output/preprocess/3/Schizophrenia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# Based on the Series summary, this is a custom panel for dopamine-regulated inflammatory genes +# So gene expression data should be available +is_gene_available = True + +# 2. Variable Availability and Data Type Conversion +# 2.1 Data Availability +# Trait (Schizophrenia) - Not available as participants are explicitly excluded if they have schizophrenia +trait_row = None + +# Age - Not extractable from characteristics dict, but background info states all participants are 35-44 years old +# Since age range is narrow and constant for all subjects, consider it not useful/available +age_row = None + +# Gender - Not in characteristics dict, but background info states all participants are males +# Since gender is constant for all subjects, consider it not useful/available +gender_row = None + +# 2.2 Data Type Conversion Functions +def convert_trait(x): + # Not used since trait data not available + return None + +def convert_age(x): + # Not used since age data not available + return None + +def convert_gender(x): + # Not used since gender data not available + return None + +# 3. Save Metadata +# Initial filtering - validate and save cohort info +validate_and_save_cohort_info( + is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=(trait_row is not None) +) + +# 4. Clinical Feature Extraction +# Skip since trait_row is None, indicating clinical data is not available +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# Looking at the gene IDs, they appear to be proper HGNC gene symbols +# e.g. ABAT, ABL1, ACAA1 which are well-known human gene symbols + +requires_gene_mapping = False +# 1. Normalize gene symbols +genetic_data = normalize_gene_symbols_in_index(genetic_data) +print("Gene data shape after normalization:", genetic_data.shape) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +genetic_data.to_csv(out_gene_data_file) + +# 2-4. Skip linking and missing value handling since no clinical data available + +# 5. Final validation - dataset cannot be used for schizophrenia study +# Note that background info explicitly states schizophrenia patients were excluded +note = "This dataset contains gene expression data but lacks information about schizophrenia status. The study explicitly excluded patients with schizophrenia in their exclusion criteria." +validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=False, + is_biased=True, # Biased since schizophrenia patients were explicitly excluded + df=genetic_data.T, # Pass transposed gene expression data as samples should be in rows + note=note +) + +# 6. Do not save linked data as the dataset is not usable for trait analysis \ No newline at end of file diff --git a/p3/preprocess/Schizophrenia/code/GSE285666.py b/p3/preprocess/Schizophrenia/code/GSE285666.py new file mode 100644 index 0000000000000000000000000000000000000000..8edd489131a442718e58150a1bce84220248fe4d --- /dev/null +++ b/p3/preprocess/Schizophrenia/code/GSE285666.py @@ -0,0 +1,164 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Schizophrenia" +cohort = "GSE285666" + +# Input paths +in_trait_dir = "../DATA/GEO/Schizophrenia" +in_cohort_dir = "../DATA/GEO/Schizophrenia/GSE285666" + +# Output paths +out_data_file = "./output/preprocess/3/Schizophrenia/GSE285666.csv" +out_gene_data_file = "./output/preprocess/3/Schizophrenia/gene_data/GSE285666.csv" +out_clinical_data_file = "./output/preprocess/3/Schizophrenia/clinical_data/GSE285666.csv" +json_path = "./output/preprocess/3/Schizophrenia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# Gene Expression Data Availability +# Yes, according to background info "Exon- and gene-Level transcriptional profiling" and "Expression analysis using Affymetrix Human Exon arrays" +is_gene_available = True + +# Clinical Data Availability and Conversion +trait_row = 0 # Found trait info in row 0 "disease state" +age_row = None # Age not available +gender_row = None # Gender not available + +def convert_trait(value: str) -> int: + """Convert disease state to binary - controls:0, patients:1""" + if pd.isna(value) or not isinstance(value, str): + return None + value = value.split(": ")[-1].lower() + if "unaffected" in value or "control" in value: + return 0 + elif "patient" in value or "williams syndrome" in value: + return 1 + return None + +# Save metadata +is_trait_available = trait_row is not None +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available) + +# Extract clinical features since trait data is available +clinical_df = geo_select_clinical_features(clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait) + +# Preview the processed clinical data +print("Preview of clinical data:") +print(preview_df(clinical_df)) + +# Save clinical data +os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True) +clinical_df.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# These appear to be numerical probe IDs, not human gene symbols +# They will need to be mapped to gene symbols before analysis +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# From observation: 'ID' in gene annotation matches gene identifiers in expression data +# 'gene_assignment' contains gene symbols in the format "RefSeq // GeneSymbol // Description" + +# Get mapping between probes and genes +mapping_df = get_gene_mapping(gene_annotation, prob_col='ID', gene_col='gene_assignment') + +# Convert probe-level data to gene-level data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +# Preview the mapped gene data +print("Gene expression data preview after mapping:") +print(gene_data.head()) +print("\nShape:", gene_data.shape) + +# Save gene data +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +# 1. Normalize gene symbols +gene_data = normalize_gene_symbols_in_index(gene_data) +print("Gene data shape after normalization:", gene_data.shape) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, gene_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "This dataset contains gene expression data from myxoid liposarcoma samples, with metastasis status as the trait." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) +else: + # Handle case where clinical features were not properly extracted + note = "Failed to extract clinical trait information from sample characteristics." + validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=False, + is_biased=None, + df=None, + note=note + ) \ No newline at end of file diff --git a/p3/preprocess/Schizophrenia/code/TCGA.py b/p3/preprocess/Schizophrenia/code/TCGA.py new file mode 100644 index 0000000000000000000000000000000000000000..542184b3c306a883cef72ed29ab5a5ea0f0b9d34 --- /dev/null +++ b/p3/preprocess/Schizophrenia/code/TCGA.py @@ -0,0 +1,28 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Schizophrenia" + +# Input paths +tcga_root_dir = "../DATA/TCGA" + +# Output paths +out_data_file = "./output/preprocess/3/Schizophrenia/TCGA.csv" +out_gene_data_file = "./output/preprocess/3/Schizophrenia/gene_data/TCGA.csv" +out_clinical_data_file = "./output/preprocess/3/Schizophrenia/clinical_data/TCGA.csv" +json_path = "./output/preprocess/3/Schizophrenia/cohort_info.json" + +# Since TCGA only contains cancer datasets, and schizophrenia is not a cancer, +# we know there won't be suitable data - record unavailability and exit +validate_and_save_cohort_info( + is_final=False, + cohort="TCGA", + info_path=json_path, + is_gene_available=False, + is_trait_available=False +) + +# Return empty dataframes to avoid errors in subsequent code +clinical_df = pd.DataFrame() +genetic_df = pd.DataFrame() \ No newline at end of file diff --git a/p3/preprocess/Schizophrenia/gene_data/GSE119289.csv b/p3/preprocess/Schizophrenia/gene_data/GSE119289.csv new file mode 100644 index 0000000000000000000000000000000000000000..60e38d5389b6ca1d80f9e7c20dbd91bde36962f4 --- /dev/null +++ b/p3/preprocess/Schizophrenia/gene_data/GSE119289.csv @@ -0,0 +1,6 @@ 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diff --git a/p3/preprocess/Schizophrenia/gene_data/GSE120340.csv b/p3/preprocess/Schizophrenia/gene_data/GSE120340.csv new file mode 100644 index 0000000000000000000000000000000000000000..2317ef5f58ed66bce71f61980c0ec0b5123d554b --- /dev/null +++ b/p3/preprocess/Schizophrenia/gene_data/GSE120340.csv @@ -0,0 +1,1172 @@ +Gene,GSM3398477,GSM3398478,GSM3398479,GSM3398480,GSM3398481,GSM3398482,GSM3398483,GSM3398484,GSM3398485,GSM3398486,GSM3398487,GSM3398488,GSM3398489,GSM3398490,GSM3398491,GSM3398492,GSM3398493,GSM3398494,GSM3398495,GSM3398496,GSM3398497,GSM3398498,GSM3398499,GSM3398500,GSM3398501,GSM3398502,GSM3398503,GSM3398504,GSM3398505,GSM3398506 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+CLEC2B,5.83065,5.94215,5.44462,5.74802,4.77258,5.47931,5.03348,7.2084,6.66281,5.51685,5.90923,5.8149,6.89332,6.83887,6.76986,9.03831,5.6263,4.89201,6.68759,6.13618,5.74206,6.97218,6.19102,5.73789,5.36662,6.18699,5.72196,5.92092,5.05378,5.34602,5.9229,7.32056,5.87509,5.84702,5.07335 +CLEC2D,4.3695,4.58821,4.28428,4.44729,4.36865,4.3586,4.47436,4.66284,4.74042,4.6448,4.36081,4.42771,4.34856,4.35853,4.62272,5.0486,4.48726,4.27987,4.61121,4.45559,4.43785,4.59589,4.47651,4.39685,4.41674,4.6355,4.31918,4.43785,4.57563,4.38404,4.42098,4.32088,4.78747,4.79652,4.35376 +CLEC3B,4.01884,4.17648,3.50972,3.929595,4.121685,3.42447,4.23545,4.251485,4.153485,4.159895,3.76455,3.99678,3.27242,4.49725,4.684245,3.712115,4.49625,3.92744,4.11539,4.32685,4.715245,2.93806,4.09837,4.34762,4.225465,4.25446,4.174595,4.45108,3.94733,3.79932,4.47885,3.94071,4.068495,3.81431,4.13727 +CLEC4A,8.793520000000001,8.3983,8.65968,8.577110000000001,8.58747,8.372150000000001,8.73742,8.662849999999999,9.14227,8.97875,8.46291,8.48827,8.79106,8.466899999999999,8.98719,8.49041,8.41002,8.427900000000001,8.53659,8.37729,8.51603,8.61017,8.56214,8.34087,8.57179,9.1844,8.686330000000002,8.503350000000001,8.33933,8.49799,8.735209999999999,8.440100000000001,8.48313,8.4153,8.66196 +CLEC4E,4.76166,4.80963,4.39497,4.4233,4.20351,4.38075,4.42635,4.54132,5.76495,4.71664,4.50882,4.90519,4.26258,4.63963,4.76036,4.82881,4.32531,4.4536,4.90078,4.57882,4.37307,4.85473,4.38128,4.38075,4.24129,5.50046,4.3214,4.4221,4.46283,4.74765,4.29036,4.31886,4.76479,4.43717,4.11366 +CLEC4M,8.28951,8.46442,8.341940000000001,8.30678,8.307120000000001,8.23958,8.39072,8.587,8.54829,8.328240000000001,8.45507,8.483979999999999,8.44829,8.28233,8.27337,8.804490000000001,8.16658,8.27928,8.500150000000001,8.30776,8.3743,8.57596,8.26642,8.193460000000002,8.32688,8.67126,8.381509999999999,8.38179,8.32667,8.661660000000001,8.161950000000001,8.23784,8.27701,8.431719999999999,8.43684 +CLEC5A,4.23919,4.52393,4.36195,4.39043,4.21109,4.31144,4.36896,4.38703,4.39517,4.51882,4.35336,4.34058,4.78987,4.36036,4.51123,4.38206,4.29083,4.29463,4.60616,4.34659,4.35336,4.27575,4.39333,4.32473,4.25166,4.67327,4.3533,4.30268,4.32376,4.39087,4.28114,6.15376,4.40725,4.35115,4.15401 +CLEC7A,4.79443,4.78112,4.78345,4.83639,4.53083,4.36428,5.06081,4.92226,5.80005,4.85639,4.33253,4.56277,4.97147,4.46494,5.16272,6.42978,4.43106,4.28881,4.60712,4.85594,4.39643,4.93422,5.08751,4.79694,4.47844,5.26842,4.36423,4.702,4.56511,4.51558,4.87114,4.87086,4.64546,4.60467,4.68468 +CLGN,5.3262,6.05249,5.78868,6.04795,5.85589,6.61087,6.06856,6.38375,5.11112,7.22013,6.88637,6.0917,5.77203,6.77346,5.84633,6.88728,6.53536,6.1921,4.87575,6.15824,5.46151,5.02102,6.48774,6.06104,6.15773,7.74788,6.85724,5.40221,6.24749,6.01886,6.76017,6.06202,6.64618,6.23475,6.06769 +CLIC1,7.88442,7.52339,7.28809,8.00403,6.6051,7.23741,6.60947,8.0457,8.67407,7.66306,7.17957,7.31755,8.33621,7.61197,8.09084,8.84438,7.65497,6.43473,7.60286,8.3161,7.52015,8.04771,7.75419,7.53708,6.88615,7.46166,7.48388,7.42807,6.94705,6.91763,7.86747,9.68492,6.54109,7.41497,7.10224 +CLIC1P1,4.88009,4.94229,4.95131,4.9549,4.85956,4.83639,5.09658,5.23108,4.8308,5.25372,5.14927,5.28248,4.79865,5.23228,4.87055,5.35299,4.78848,4.6397,5.28063,5.14314,4.94229,5.27778,4.90475,4.92769,4.60157,5.45324,4.90366,4.76427,4.91674,4.94229,4.93953,4.6887,5.46411,5.00638,4.87352 +CLIC2,5.08592,5.06776,5.33353,5.27881,5.23346,5.36531,5.17972,5.52067,5.42683,5.35048,5.76131,5.25795,5.72493,5.52123,5.7658,5.47321,5.34111,5.304,5.34128,5.28848,5.23568,5.09711,5.27262,5.4378,5.38454,5.62745,5.97171,5.64401,5.38438,5.28933,5.66886,6.16408,5.48711,5.02766,5.48441 +CLIC3,4.16184,4.55446,4.37348,4.6495,4.41051,4.50257,4.63327,4.66118,4.60259,4.56243,4.57084,4.81761,4.26806,4.57838,4.56243,4.90092,4.65227,4.67508,4.54037,4.42785,4.6094,4.7458,4.54339,4.62036,4.36814,5.09418,4.55436,4.22155,4.6684,4.66108,4.67207,4.57293,4.55766,4.36692,4.54216 +CLIC4,22.915869999999998,22.75174,19.6939,19.94236,19.868570000000002,18.867539999999998,18.14546,20.51536,24.93419,20.15065,19.14629,20.8398,21.94042,20.624579999999998,19.86331,21.16869,22.187549999999998,20.51566,21.07499,22.304699999999997,21.31468,21.99955,21.94121,21.2809,21.052059999999997,21.81842,19.87007,20.57645,20.72685,19.3993,20.912480000000002,24.86334,19.29421,21.09585,21.58338 +CLIC5,14.70503,14.52418,14.76427,15.3278,15.70569,14.74702,16.19451,15.68535,15.67849,15.87313,15.49659,15.4521,14.87689,15.50249,14.98003,15.536,15.056840000000001,15.26186,15.966650000000001,15.55648,15.78181,15.49806,15.062159999999999,15.429310000000001,15.12577,16.25518,15.07167,15.419830000000001,14.69322,15.574839999999998,15.45504,14.304359999999999,15.81781,15.4363,15.14526 +CLINT1,16.158360000000002,15.79402,16.32667,15.76254,16.22813,16.7045,15.1501,16.44582,14.702639999999999,16.29469,16.56803,15.98998,16.427950000000003,16.38016,16.33694,16.36713,16.30019,16.59314,15.161290000000001,16.44809,15.69897,15.448879999999999,16.29914,16.11724,16.52236,16.11634,16.9477,16.25073,16.54013,15.7821,16.41265,16.36119,15.81963,16.41476,16.53219 +CLIP1,15.99532,14.71014,15.949560000000002,16.35013,16.72147,17.48696,16.023139999999998,15.32216,14.50627,16.45742,16.84007,14.67446,17.6023,16.37367,15.26334,15.85267,16.601419999999997,16.90079,16.201639999999998,16.414279999999998,16.13802,15.54496,15.55002,17.229680000000002,17.25089,15.71526,17.128790000000002,15.91591,17.21819,15.13746,16.66628,17.61466,15.223849999999999,15.93181,17.45413 +CLIP2,8.98666,8.9586,8.92977,9.37305,8.83899,8.58858,9.82119,7.87139,9.4778,7.31221,8.33931,8.86388,8.5709,8.48921,8.19892,7.04827,8.79247,8.51996,8.62844,8.25281,9.64681,9.57946,8.665,8.84329,8.75663,7.1133,7.88479,8.99603,8.90287,9.11196,8.58171,8.73163,8.76809,8.63931,8.68844 +CLIP3,9.86076,9.62895,10.1981,10.6989,10.7658,10.1094,10.8505,9.28923,9.36852,8.19556,9.61422,9.7591,10.1799,9.71908,9.56332,8.75084,10.5185,10.3412,10.0026,9.71454,10.82,10.1914,9.82119,10.3214,10.3748,8.61308,9.8026,10.5621,10.3175,9.81466,10.353,10.3374,9.96454,9.44306,10.3135 +CLIP4,5.62351,5.73946,5.88023,5.53368,5.99281,5.72991,5.63702,5.69289,5.8847,6.12398,5.69346,5.71798,5.99976,5.79056,5.68708,6.01538,5.88501,6.07364,5.97116,5.85469,5.50262,5.78346,5.78346,5.89125,5.96462,5.68947,5.83187,5.72171,5.81916,5.72702,5.88393,6.05798,5.74289,5.52452,5.74018 +CLK1,9.45971,9.94368,9.16133,8.29246,9.43123,8.8561,8.98878,8.70204,10.2346,8.50103,9.3353,8.99289,9.88296,8.66313,9.34777,8.61568,9.07933,9.30859,8.51035,8.46869,9.48163,8.3305,8.58344,9.39818,9.28254,8.07732,8.97272,8.82471,9.0911,9.26705,8.88844,9.68257,8.74768,9.86655,9.15907 +CLK2,7.14523,7.44408,7.19858,7.42791,7.83667,7.00915,7.78354,7.12532,7.55702,7.10538,7.09267,7.29101,7.57856,6.93139,6.94948,6.99118,7.42865,7.47721,7.13784,7.1059,7.68241,7.27473,7.19987,7.75801,7.83559,7.43784,6.90212,7.30227,6.97591,7.27473,7.17752,7.61514,7.20368,7.15734,7.57553 +CLK3,6.57149,6.75681,6.80729,6.89705,6.59556,6.47966,6.46986,6.61838,7.14947,6.40364,6.63854,6.4924,6.98501,6.52103,6.39768,6.09518,6.6943,6.66008,6.51224,6.61158,6.67376,6.43755,6.51098,6.65676,6.79033,6.27768,6.12781,6.78358,6.76759,6.30267,6.49087,6.81297,6.3684,6.45358,6.61838 +CLK4,8.02581,8.65826,8.12806,8.11019,8.73036,8.14635,8.66939,8.1128,8.43669,8.39226,8.53546,7.8841,8.89807,7.99828,8.29463,7.98542,8.1635,8.47083,8.05524,7.59403,8.66937,8.20039,7.67188,8.398,8.48274,8.18782,8.32878,7.95414,8.29463,8.94413,7.95051,8.44009,8.16252,8.49582,8.31238 +CLMN,13.34683,14.98114,12.14273,12.2534,12.82735,11.4829,11.84877,11.800419999999999,15.40348,11.995840000000001,11.63509,12.42263,12.92041,11.42485,12.266829999999999,12.252839999999999,13.3374,11.797329999999999,10.889389999999999,12.26976,13.723669999999998,11.85984,14.46735,11.45666,12.24141,11.95024,11.39939,12.362639999999999,13.6247,12.11623,12.2371,12.947330000000001,11.764800000000001,13.229330000000001,13.164719999999999 +CLN3,11.86652,11.66375,11.61116,11.373660000000001,11.83866,11.64423,11.21789,10.93413,12.206620000000001,10.699580000000001,11.46837,11.301079999999999,11.9991,11.40815,11.2025,11.285,12.10397,11.75441,11.06295,11.27496,12.30751,11.76624,11.757670000000001,11.83848,12.072189999999999,11.02041,11.29748,11.65592,11.77575,11.242840000000001,11.794820000000001,11.810210000000001,11.36815,11.21909,11.906870000000001 +CLN5,20.69427,22.91207,20.47891,19.10965,19.139760000000003,20.4831,18.61663,22.23543,19.75687,20.62639,20.98604,20.50513,19.97922,21.91669,18.74712,23.02229,20.89511,21.05455,20.61276,23.73809,20.56513,20.304859999999998,22.4081,19.657049999999998,20.53921,21.58805,21.79953,20.91417,19.94627,20.457720000000002,22.07236,21.7148,20.55067,22.16958,20.04162 +CLN6,6.20204,6.47948,6.47155,6.50885,6.27269,6.3797,6.82043,6.26273,6.16794,6.40526,6.49476,6.20568,6.30515,6.22527,6.27269,5.99108,6.39685,6.16437,6.63504,6.27407,6.39086,6.35485,6.17508,6.16961,6.13897,6.05848,6.23989,6.32545,6.20588,6.30637,6.14114,6.20423,6.44096,6.22279,6.26483 +CLN8,13.64688,14.5106,12.96961,12.57374,13.01576,12.22133,12.43314,11.99091,14.77461,11.56513,12.000060000000001,13.23823,13.115120000000001,12.74216,12.77918,11.503820000000001,13.711310000000001,12.93946,12.937380000000001,12.876650000000001,13.739650000000001,12.51009,13.26469,12.26278,12.82621,12.338429999999999,11.94078,13.05184,13.49406,12.782589999999999,12.61036,13.60295,12.149709999999999,12.969100000000001,13.52517 +CLNS1A,9.924,10.0143,10.0832,9.29991,9.20228,9.65979,9.08691,9.99442,10.0339,10.3146,10.1426,10.1587,9.44914,10.0549,9.84094,9.97659,9.75627,9.55068,9.96364,9.98545,9.53753,9.82641,9.90216,9.4418,9.37647,9.64204,9.74564,9.67549,9.75339,10.0648,9.79681,9.38755,10.0026,10.1931,9.47776 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+NBPF14,6.779298392857143,6.5395125,6.332542500000001,6.185377535714286,6.461194214285714,6.323003464285714,6.12277675,6.2938553214285715,6.950650428571429,6.259109107142857,6.2465356071428575,6.370091107142857,6.6545198928571425,6.531434071428571,6.47326925,6.2859900714285715,6.403711107142858,6.555602071428572,7.073505285714285,6.624062107142858,6.619775571428572,6.526910428571428,6.325915571428571,6.644090714285714,6.887326535714285,6.4849130357142855,6.182114821428572,6.306207678571429,6.403422964285714,6.397517928571428,6.226025285714286,6.411068571428571,6.379583928571429,6.327733142857142,6.672913357142857 +NBPF15,4.634813392857143,4.4839875,4.347017500000001,4.166895035714285,4.414919214285715,4.362920964285714,4.17576925,4.432637821428571,4.8009704285714285,4.3857116071428575,4.439155607142857,4.467708607142857,4.517449892857143,4.484334071428571,4.45627675,4.461765071428571,4.389176107142857,4.441672071428572,4.821275285714286,4.539877107142857,4.5743605714285716,4.526030428571429,4.381143071428571,4.614605714285714,4.599974035714286,4.436678035714285,4.286019821428571,4.3074401785714285,4.405367964285714,4.508220428571429,4.366462785714286,4.504801071428571,4.423691428571429,4.4390756428571425,4.529330857142857 +NBPF19,1.92271,1.8479228571428572,1.781592142857143,1.7064741428571428,1.8145752857142856,1.791404,1.6198730000000001,1.795128,1.9711811428571429,1.8331428571428572,1.7412682857142856,1.7959741428571427,1.8838425714285716,1.8366015714285715,1.8402144285714286,1.8230954285714285,1.800742,1.8865245714285717,1.992786,1.8790330000000002,1.8239177142857144,1.7536768571428571,1.7571555714285714,1.859387857142857,1.934966,1.8656742857142856,1.7551092857142856,1.7923307142857143,1.811471,1.730656142857143,1.7742645714285712,1.8013385714285715,1.7963264285714287,1.7915081428571429,1.8977394285714286 +NBPF20,3.5271333928571424,3.398144642857143,3.325810357142857,3.1323578928571427,3.374334928571429,3.3512009642857143,3.2368492499999997,3.421827821428572,3.6553932857142857,3.32717875,3.4552113214285716,3.429951464285714,3.4083713214285716,3.4214054999999997,3.3918053214285715,3.3901736428571425,3.356196107142857,3.3503935,3.6375152857142856,3.465527107142857,3.523584857142857,3.5123275714285715,3.3767345,3.5680428571428573,3.481904035714286,3.36858375,3.2752055357142855,3.2723744642857144,3.3696579642857145,3.5281032857142858,3.391314214285714,3.5292424999999996,3.37346,3.4342284999999997,3.4337894285714285 +NBPF25P,0.8150299999999999,0.76208,0.7603850000000001,0.671937,0.773991,0.779684,0.6809529999999999,0.7843180000000001,0.825604,0.77461,0.757324,0.7582169999999999,0.774764,0.7736729999999999,0.7757430000000001,0.751504,0.7677620000000001,0.795246,0.809026,0.804683,0.773142,0.739974,0.752747,0.8128249999999999,0.8168960000000001,0.79758,0.7442949999999999,0.7572650000000001,0.7757609999999999,0.7505390000000001,0.7991159999999999,0.82578,0.7460950000000001,0.7866609999999999,0.802198 +NBPF26,4.067195,3.903447857142857,3.767117142857143,3.724956642857143,3.860850285714286,3.7514865,3.5668805,3.6563455,4.120861142857143,3.706540357142857,3.5486482857142856,3.698356642857143,4.020912571428572,3.8837015714285714,3.857206928571429,3.6473204285714287,3.815277,4.0004545714285715,4.245016,3.9632180000000004,3.8693327142857146,3.754556857142857,3.701928071428571,3.8888728571428572,4.2223185,3.9139092857142854,3.651204285714286,3.7910982142857144,3.809526,3.6199536428571433,3.633827071428571,3.7076060714285712,3.7522189285714287,3.680165642857143,4.041321928571429 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+NBPF9,5.671618392857143,5.453669642857143,5.311335357142857,5.150840392857143,5.420609928571428,5.311283464285714,5.18385675,5.283045321428571,5.805073285714286,5.20057625,5.262591321428571,5.332333964285715,5.545441321428571,5.468505499999999,5.408797821428571,5.214398642857143,5.370731107142857,5.4643235,5.889745285714286,5.549712107142858,5.568999857142858,5.5132075714285715,5.321507,5.5975278571428575,5.769256535714286,5.41681875,5.171300535714286,5.2711419642857145,5.367712964285714,5.417400785714285,5.250876714285714,5.43551,5.329352500000001,5.322886,5.577371928571429 +NBR1,16.56127,15.654530000000001,16.10344,14.87631,15.73689,16.34027,14.23365,14.64817,16.77822,13.87167,15.72885,14.79431,16.71519,15.61926,14.90595,13.65221,16.8242,16.64425,16.04293,16.57171,16.2645,15.11001,15.876460000000002,16.49019,17.12051,13.37676,15.97818,15.74363,16.6914,14.89174,16.97741,16.735300000000002,14.86385,15.435490000000001,17.31361 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+NCF1C,1.7301233333333332,1.6936966666666666,1.76319,1.7132333333333334,1.7405099999999998,1.7101233333333334,1.8310833333333332,1.7014233333333333,1.7279,1.9067166666666668,1.7611933333333332,1.6867566666666667,1.8894866666666665,1.6804,1.6892833333333332,1.7340666666666669,1.7004133333333333,1.7098066666666665,1.7473766666666668,1.74597,1.68734,1.6712866666666668,1.7742766666666665,1.7472266666666665,1.7356066666666665,1.7405099999999998,1.7957533333333335,1.7253299999999998,1.81655,1.7043333333333335,1.7529066666666668,1.72075,1.7405099999999998,1.7374933333333333,1.8013733333333333 +NCF2,4.70133,4.32315,4.42342,4.5689,4.35393,4.42665,4.75155,4.65231,5.08925,4.65401,4.5146,4.63935,5.25881,4.75324,4.89216,5.38016,4.58944,4.44056,5.17968,4.79478,4.39684,4.75778,4.83022,4.65401,4.46333,4.97948,4.54986,4.58602,4.51622,4.74018,4.58932,5.13905,5.23578,4.65401,4.60798 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diff --git a/p3/preprocess/Sickle_Cell_Anemia/GSE53441.csv b/p3/preprocess/Sickle_Cell_Anemia/GSE53441.csv new file mode 100644 index 0000000000000000000000000000000000000000..11aefb5050cf608145d1201883e59600b850b858 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/GSE53441.csv @@ -0,0 +1,35 @@ 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CAR4,BCAS1,BCAS2,BCAS3,BCAS4,BCAT1,BCAT2,BCCIP,BCDIN3D,BCHE,BCKDHA,BCKDHB,BCKDK,BCL10,BCL11A,BCL11B,BCL2,BCL2A1,BCL2L1,BCL2L10,BCL2L11,BCL2L12,BCL2L13,BCL2L14,BCL2L15,BCL2L2,BCL3,BCL6,BCL6B,BCL7A,BCL7B,BCL7C,BCL9,BCL9L,BCLAF1,BCO1,BCO2,BCOR,BCORL1,BCORP1,BCR,BCRP3,BCS1L,BDH1,BDH2,BDKRB1,BDKRB2,BDNF,BDNF-AS,BDP1,BEAN1,BECN1,BEGAIN,BEND2,BEND3,BEND4,BEND5,BEND6,BEND7,BEST1,BEST2,BEST3,BEST4,BET1,BET1L,BEX1,BEX2,BEX3,BEX4,BEX5,BFAR,BFSP1,BFSP2,BFSP2-AS1,BGLAP,BGLT3,BGN,BHLHE22,BHLHE23,BHLHE40,BHLHE41,BHMT,BHMT2,BICC1,BICD1,BICD2,BICDL1,BICDL2,BICRA,BICRAL,BID,BIK,BIN1,BIN2,BIN3,BIN3-IT1,BIRC2,BIRC3,BIRC5,BIRC6,BIRC7,BIVM,BLACAT1,BLCAP,BLID,BLK,BLM,BLMH,BLNK,BLOC1S1,BLOC1S2,BLOC1S3,BLOC1S4,BLOC1S5,BLOC1S6,BLTP1,BLTP2,BLTP3A,BLTP3B,BLVRA,BLVRB,BLZF1,BMAL1,BMAL2,BMAL2-AS1,BMERB1,BMF,BMI1,BMP1,BMP10,BMP15,BMP2,BMP2K,BMP3,BMP4,BMP5,BMP6,BMP7,BMP8A,BMP8B,BMPER,BMPR1A,BMPR1B,BMPR2,BMS1,BMS1P1,BMS1P17,BMS1P18,BMS1P2,BMS1P20,BMX,BNC1,BNC2,BNIP1,BNIP2,BNIP3,BNIP3L,BNIPL,BOC,BOD1,BOD1L1,BOD1L2,BOK,BOLA1,BOLA2,BOLA2B,BOLA3,BOLA3-DT,BOLL,BOP1,BORA,BORCS5,BORCS6,BORCS7,BORCS8,BPESC1,BPGM,BPHL,BPI,BPIFA1,BPIFA2,BPIFA3,BPIFA4P,BPIFB1,BPIFB2,BPIFB4,BPIFB6,BPIFB9P,BPIFC,BPNT1,BPNT2,BPTF,BPY2,BRAF,BRAP,BRAT1,BRCA1,BRCA2,BRCC3,BRD1,BRD10,BRD2,BRD3,BRD4,BRD7,BRD7P3,BRD8,BRD9,BRDT,BRF1,BRF2,BRI3,BRI3BP,BRICD5,BRINP1,BRINP2,BRINP3,BRIP1,BRIX1,BRK1,BRME1,BRMS1,BRMS1L,BROX,BRPF1,BRPF3,BRS3,BRSK1,BRSK2,BRWD1,BRWD1-AS2,BRWD3,BSCL2,BSDC1,BSG,BSN,BSN-DT,BSND,BSPRY,BST1,BST2,BTAF1,BTBD1,BTBD10,BTBD16,BTBD17,BTBD18,BTBD19,BTBD2,BTBD3,BTBD6,BTBD7,BTBD8,BTBD9,BTC,BTD,BTF3,BTF3L4,BTF3P11,BTF3P12,BTF3P13,BTG1,BTG2,BTG3,BTG4,BTK,BTLA,BTN1A1,BTN2A1,BTN2A2,BTN2A3P,BTN3A1,BTN3A2,BTN3A3,BTNL2,BTNL3,BTNL8,BTNL9,BTRC,BUB1,BUB1B,BUB3,BUD13,BUD23,BUD31,BYSL,BZW1,BZW2,C10orf126,C10orf53,C10orf55,C10orf62,C10orf67,C10orf71,C10orf88,C10orf90,C10orf95,C10orf95-AS1,C11orf16,C11orf21,C11orf24,C11orf40,C11orf42,C11orf54,C11orf58,C11orf65,C11orf68,C11orf71,C11orf86,C11orf87,C11orf96,C11orf97,C11orf98,C12orf42,C12orf43,C12orf50,C12orf54,C12orf56,C12orf57,C12orf60,C12orf75,C12orf76,C14orf119,C14orf132,C14orf180,C14orf39,C14orf93,C15orf32,C15orf39,C15orf40,C15orf48,C15orf61,C15orf62,C16orf46,C16orf54,C16orf74,C16orf78,C16orf82,C16orf86,C16orf87,C16orf89,C16orf92,C16orf95,C17orf100,C17orf50,C17orf58,C17orf67,C17orf75,C17orf78,C17orf99,C18orf15,C18orf21,C18orf32,C18orf54,C18orf61,C19orf12,C19orf18,C19orf25,C19orf33,C19orf44,C19orf47,C19orf48P,C19orf53,C19orf73,C19orf81,C19orf84,C1D,C1GALT1,C1GALT1C1,C1QA,C1QB,C1QBP,C1QC,C1QL1,C1QTNF1,C1QTNF12,C1QTNF2,C1QTNF3,C1QTNF4,C1QTNF5,C1QTNF6,C1QTNF7,C1QTNF9,C1QTNF9B,C1R,C1RL,C1RL-AS1,C1S,C1orf105,C1orf115,C1orf116,C1orf122,C1orf159,C1orf162,C1orf167,C1orf174,C1orf198,C1orf21,C1orf210,C1orf216,C1orf220,C1orf226,C1orf35,C1orf43,C1orf50,C1orf52,C1orf53,C1orf54,C1orf56,C1orf74,C1orf87,C1orf94,C2,C20orf141,C20orf144,C20orf173,C20orf181,C20orf202,C20orf203,C20orf96,C21orf58,C21orf91,C22orf15,C22orf23,C22orf31,C22orf39,C22orf42,C22orf46P,C2CD2,C2CD2L,C2CD3,C2CD4A,C2CD4B,C2CD4C,C2CD5,C2CD6,C2orf15,C2orf42,C2orf49,C2orf68,C2orf69,C2orf72,C2orf74,C2orf76,C2orf80,C2orf81,C2orf88,C3,C3AR1,C3P1,C3orf18,C3orf20,C3orf22,C3orf33,C3orf36,C3orf38,C3orf49,C3orf52,C3orf62,C3orf70,C3orf80,C4A,C4B,C4BPA,C4BPB,C4orf17,C4orf33,C4orf36,C4orf46,C5,C5AR1,C5AR2,C5orf15,C5orf22,C5orf24,C5orf34,C5orf46,C5orf47,C5orf58,C5orf63,C6,C6orf118,C6orf120,C6orf132,C6orf136,C6orf141,C6orf147,C6orf15,C6orf163,C6orf47,C6orf52,C6orf58,C6orf62,C6orf89,C7,C7orf25,C7orf33,C7orf57,C8A,C8B,C8G,C8orf17,C8orf33,C8orf34,C8orf44,C8orf48,C8orf58,C8orf74,C8orf76,C8orf82,C8orf88,C9,C9orf152,C9orf163,C9orf40,C9orf43,C9orf50,C9orf57,C9orf72,C9orf78,C9orf85,CA1,CA10,CA11,CA12,CA13,CA14,CA2,CA3,CA4,CA5A,CA5B,CA5BP1,CA6,CA7,CA8,CA9,CAAP1,CAB39,CAB39L,CABCOCO1,CABIN1,CABLES1,CABLES2,CABP1,CABP2,CABP4,CABP5,CABP7,CABS1,CABYR,CACFD1,CACHD1,CACNA1A,CACNA1B,CACNA1C,CACNA1D,CACNA1E,CACNA1F,CACNA1G,CACNA1H,CACNA1I,CACNA1S,CACNA2D1,CACNA2D2,CACNA2D3,CACNA2D4,CACNB1,CACNB2,CACNB3,CACNB4,CACNG1,CACNG2,CACNG3,CACNG4,CACNG5,CACNG6,CACNG7,CACNG8,CACTIN,CACUL1,CACYBP,CAD,CADM1,CADM2,CADM2-AS1,CADM3,CADM3-AS1,CADM4,CADPS,CADPS2,CAGE1,CAHM,CALB1,CALB2,CALCA,CALCB,CALCOCO1,CALCOCO2,CALCR,CALCRL,CALD1,CALHM1,CALHM2,CALHM3,CALHM4,CALHM5,CALHM6,CALM1,CALM2,CALM3,CALML3,CALML4,CALML5,CALML6,CALN1,CALR,CALR3,CALU,CALY,CAMK1,CAMK1D,CAMK1G,CAMK2A,CAMK2B,CAMK2D,CAMK2G,CAMK2N1,CAMK2N2,CAMK4,CAMKK1,CAMKK2,CAMKMT,CAMKV,CAMLG,CAMP,CAMSAP1,CAMSAP2,CAMSAP3,CAMTA1,CAMTA2,CAND1,CAND2,CANT1,CANX,CAP1,CAP2,CAPG,CAPN1,CAPN10,CAPN10-DT,CAPN11,CAPN12,CAPN13,CAPN14,CAPN15,CAPN2,CAPN3,CAPN5,CAPN6,CAPN7,CAPN8,CAPN9,CAPNS1,CAPNS2,CAPRIN1,CAPRIN2,CAPS,CAPS2,CAPSL,CAPZA1,CAPZA2,CAPZA3,CAPZB,CARD10,CARD11,CARD14,CARD16,CARD18,CARD19,CARD6,CARD8,CARD9,CARF,CARHSP1,CARINH,CARM1,CARMIL1,CARMIL2,CARMIL3,CARMN,CARNMT1,CARNS1,CARS1,CARS1-AS1,CARS2,CARTPT,CASC11,CASC15,CASC16,CASC17,CASC18,CASC2,CASC22,CASC3,CASC6,CASD1,CASK,CASKIN1,CASKIN2,CASP1,CASP10,CASP12,CASP14,CASP16P,CASP2,CASP3,CASP4,CASP5,CASP6,CASP7,CASP8,CASP8AP2,CASP9,CASQ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A1,FUCA2,FUNDC1,FUNDC2,FUOM,FURIN,FUS,FUT1,FUT10,FUT11,FUT2,FUT3,FUT4,FUT5,FUT6,FUT7,FUT8,FUT8-AS1,FUT9,FUZ,FXN,FXR1,FXR2,FXYD1,FXYD2,FXYD3,FXYD4,FXYD5,FXYD6,FXYD7,FYB1,FYB2,FYCO1,FYN,FYTTD1,FZD1,FZD10,FZD10-AS1,FZD2,FZD3,FZD4,FZD5,FZD6,FZD7,FZD8,FZD9,FZR1,G0S2,G2E3,G3BP1,G3BP2,G6PC1,G6PC2,G6PC3,G6PD,GAA,GAB1,GAB2,GAB3,GAB4,GABARAP,GABARAPL1,GABARAPL2,GABARAPL3,GABBR1,GABBR2,GABPA,GABPB1,GABPB1-AS1,GABPB2,GABRA1,GABRA2,GABRA3,GABRA4,GABRA5,GABRA6,GABRB1,GABRB2,GABRB3,GABRD,GABRE,GABRG1,GABRG2,GABRG3,GABRP,GABRQ,GABRR1,GABRR2,GABRR3,GAD1,GAD2,GADD45A,GADD45B,GADD45G,GADD45GIP1,GADL1,GAGE1,GAGE12B,GAGE12C,GAGE12D,GAGE12E,GAGE12F,GAGE12G,GAGE12H,GAGE12I,GAGE12J,GAGE13,GAGE2A,GAGE2B,GAGE2C,GAGE2D,GAGE2E,GAGE4,GAGE5,GAGE6,GAGE7,GAGE8,GAK,GAL,GAL3ST1,GAL3ST2,GAL3ST3,GAL3ST4,GALC,GALE,GALK1,GALK2,GALM,GALNS,GALNT1,GALNT10,GALNT11,GALNT12,GALNT13,GALNT14,GALNT15,GALNT16,GALNT17,GALNT18,GALNT2,GALNT3,GALNT4,GALNT5,GALNT6,GALNT7,GALNT8,GALNT9,GALNTL5,GALNTL6,GALP,GALR1,GALR2,GALR3,GALT,GAMT,GAN,GANAB,GANC,GAP43,GAPDH,GAPDHP62,GAPDHP73,GAPDHS,GAPT,GAPVD1,GAR1,GAREM1,GAREM2,GARIN1A,GARIN1B,GARIN2,GARIN3,GARIN4,GARIN5A,GARIN5B,GARIN6,GARNL3,GARRE1,GART,GAS1,GAS2,GAS2L1,GAS2L2,GAS2L3,GAS5,GAS5-AS1,GAS6,GAS6-AS1,GAS7,GAS8,GAS8-AS1,GASK1A,GASK1B,GAST,GATA1,GATA2,GATA3,GATA3-AS1,GATA4,GATA5,GATA6,GATA6-AS1,GATAD1,GATAD2A,GATAD2B,GATB,GATC,GATD1,GATD1-DT,GATD3,GATM,GBA1LP,GBA2,GBA3,GBE1,GBF1,GBGT1,GBP1,GBP1P1,GBP2,GBP3,GBP4,GBP5,GBP6,GBX1,GBX2,GC,GCA,GCAT,GCC1,GCC2,GCDH,GCFC2,GCG,GCGR,GCH1,GCHFR,GCK,GCKR,GCLC,GCLM,GCM1,GCM2,GCN1,GCNA,GCNT1,GCNT1P1,GCNT2,GCNT3,GCNT4,GCNT7,GCOM1,GCSAM,GCSAML,GCSAML-AS1,GCSH,GDA,GDAP1,GDAP1L1,GDAP2,GDE1,GDF1,GDF10,GDF11,GDF15,GDF2,GDF3,GDF5,GDF9,GDI1,GDI2,GDNF,GDPD1,GDPD2,GDPD3,GDPD5,GDPGP1,GEM,GEMIN2,GEMIN4,GEMIN5,GEMIN6,GEMIN7,GEMIN8,GEN1,GET1,GET3,GET4,GFAP,GFER,GFI1,GFI1B,GFM1,GFM2,GFOD1,GFOD2,GFOD3P,GFPT1,GFPT2,GFRA1,GFRA2,GFRA3,GFRA4,GFUS,GGA1,GGA2,GGA3,GGACT,GGCT,GGCX,GGH,GGN,GGNBP2,GGPS1,GGT1,GGT3P,GGT5,GGT6,GGT7,GGT8P,GGTA2P,GGTLC1,GGTLC2,GH1,GH2,GHDC,GHET1,GHITM,GHR,GHRH,GHRHR,GHRL,GHRLOS,GHSR,GID4,GID8,GIGYF1,GIGYF2,GIMAP1,GIMAP2,GIMAP4,GIMAP5,GIMAP6,GIMAP7,GIMAP8,GIN1,GINM1,GINS1,GINS2,GINS3,GINS4,GIP,GIPC1,GIPC2,GIPC3,GIPR,GIT1,GIT2,GJA1,GJA10,GJA3,GJA4,GJA5,GJA8,GJA9,GJA9-MYCBP,GJB1,GJB2,GJB3,GJB4,GJB5,GJB6,GJC1,GJC2,GJD2,GJD3,GJD4,GK,GK-AS1,GK2,GK3,GK5,GKAP1,GKN1,GKN2,GLA,GLB1,GLB1L,GLB1L2,GLB1L3,GLCCI1,GLCE,GLDC,GLDN,GLE1,GLG1,GLI1,GLI2,GLI3,GLI4,GLIDR,GLIPR1,GLIPR1L1,GLIPR2,GLIS1,GLIS2,GLIS3,GLIS3-AS1,GLMN,GLMP,GLO1,GLOD4,GLOD5,GLP1R,GLP2R,GLRA1,GLRA2,GLRA3,GLRB,GLRX,GLRX2,GLRX3,GLRX5,GLS,GLS2,GLT1D1,GLT8D1,GLT8D2,GLTP,GLTPD2,GLUD1,GLUD2,GLUL,GLULP4,GLYAT,GLYATL1,GLYATL2,GLYCTK,GLYCTK-AS1,GLYR1,GM2A,GMCL1,GMCL2,GMDS,GMDS-DT,GMEB1,GMEB2,GMFB,GMFG,GMIP,GML,GMNC,GMNN,GMPPA,GMPPB,GMPR,GMPR2,GMPS,GNA11,GNA12,GNA13,GNA14,GNA14-AS1,GNA15,GNAI1,GNAI2,GNAI3,GNAL,GNAO1,GNAQ,GNAS,GNAS-AS1,GNAT1,GNAT2,GNAT3,GNAZ,GNB1,GNB1L,GNB2,GNB3,GNB4,GNB5,GNE,GNG10,GNG11,GNG12,GNG13,GNG2,GNG3,GNG4,GNG5,GNG7,GNG8,GNGT1,GNGT2,GNL1,GNL2,GNL3,GNL3L,GNLY,GNMT,GNPAT,GNPDA1,GNPDA2,GNPNAT1,GNPTAB,GNPTG,GNRH1,GNRH2,GNRHR,GNRHR2,GNS,GOLGA1,GOLGA2,GOLGA2P2Y,GOLGA2P3Y,GOLGA2P5,GOLGA2P7,GOLGA3,GOLGA4,GOLGA5,GOLGA6A,GOLGA6B,GOLGA6C,GOLGA6D,GOLGA6L1,GOLGA6L11P,GOLGA6L16P,GOLGA6L2,GOLGA6L22,GOLGA6L4,GOLGA6L5P,GOLGA6L6,GOLGA6L9,GOLGA7,GOLGA7B,GOLGA8A,GOLGA8B,GOLGA8CP,GOLGA8DP,GOLGA8EP,GOLGA8F,GOLGA8G,GOLGA8IP,GOLGA8M,GOLGA8N,GOLGB1,GOLIM4,GOLM1,GOLM2,GOLPH3,GOLPH3L,GOLT1A,GOLT1B,GON4L,GON7,GOPC,GORAB,GORASP1,GORASP2,GOSR1,GOSR2,GOT1,GOT1L1,GOT2,GOT2P1,GP1BA,GP1BB,GP2,GP5,GP6,GP9,GPA33,GPAA1,GPALPP1,GPAM,GPANK1,GPAT2,GPAT3,GPAT4,GPATCH1,GPATCH11,GPATCH2,GPATCH2L,GPATCH3,GPATCH4,GPATCH8,GPBAR1,GPBP1,GPBP1L1,GPC1,GPC2,GPC3,GPC4,GPC5,GPC6,GPCPD1,GPD1,GPD1L,GPD2,GPER1,GPHA2,GPHB5,GPHN,GPI,GPIHBP1,GPKOW,GPLD1,GPM6A,GPM6B,GPN1,GPN2,GPN3,GPNMB,GPR101,GPR107,GPR108,GPR12,GPR132,GPR135,GPR137,GPR137B,GPR137C,GPR143,GPR146,GPR15,GPR150,GPR153,GPR155,GPR156,GPR157,GPR158,GPR15LG,GPR160,GPR161,GPR162,GPR17,GPR171,GPR173,GPR174,GPR176,GPR18,GPR180,GPR182,GPR183,GPR19,GPR20,GPR21,GPR22,GPR25,GPR26,GPR27,GPR3,GPR31,GPR32,GPR34,GPR35,GPR37,GPR37L1,GPR39,GPR4,GPR42,GPR45,GPR50,GPR52,GPR55,GPR6,GPR61,GPR62,GPR63,GPR65,GPR68,GPR75,GPR75-ASB3,GPR78,GPR82,GPR83,GPR84,GPR85,GPR87,GPR88,GPR89A,GPR89B,GPRASP1,GPRASP2,GPRC5A,GPRC5B,GPRC5C,GPRC5D,GPRC6A,GPRIN1,GPRIN2,GPRIN3,GPS1,GPS2,GPSM1,GPSM2,GPSM3,GPT,GPT2,GPX1,GPX2,GPX3,GPX4,GPX5,GPX7,GPX8,GRAMD1A,GRAMD1B,GRAMD1C,GRAMD2A,GRAMD2B,GRAMD4,GRAP,GRAP2,GRAPL,GRB10,GRB14,GRB2,GRB7,GREB1,GREB1L,GREM1,GREM2,GRHL1,GRHL2,GRHL3,GRHPR,GRIA1,GRIA2,GRIA3,GRIA4,GRID1,GRID1-AS1,GRID2,GRIK1,GRIK1-AS1,GRIK1-AS2,GRIK2,GRIK3,GRIK4,GRIK5,GRIN1,GRIN2A,GRIN2B,GRIN2C,GRIN2D,GRIN3A,GRIN3B,GRINA,GRIP1,GRIP2,GRIPAP1,GRK1,GRK2,GRK3,GRK4,GRK5,GRK6,GRK7,GRM1,GRM2,GRM3,GRM4,GRM5,GRM6,GRM7,GRM8,GRN,GRP,GRPEL1,GRPEL2,GRPR,GRSF1,GRTP1,GRTP1-AS1,GRWD1,GSAP,GSC,GSC2,GSDMB,GSDMC,GSDMD,GSDME,GSE1,GSG1,GSG1L,GSK3A,GSK3B,GSKIP,GSN,GSN-AS1,GSPT1,GSPT2,GSR,GSS,GSTA1,GSTA3,GSTA4,GSTCD,GSTK1,GSTM1,GSTM2,GSTM3,GSTM4,GSTM5,GSTO1,GSTO2,G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BP4P4,RBBP5,RBBP6,RBBP7,RBBP8,RBBP8NL,RBBP9,RBCK1,RBFA,RBFADN,RBFOX1,RBFOX2,RBFOX3,RBIS,RBKS,RBL1,RBL2,RBM10,RBM11,RBM12,RBM12B,RBM12B-AS1,RBM14,RBM14-RBM4,RBM15,RBM15B,RBM17,RBM18,RBM19,RBM20,RBM22,RBM23,RBM24,RBM25,RBM26,RBM26-AS1,RBM27,RBM28,RBM3,RBM33,RBM34,RBM38,RBM39,RBM4,RBM41,RBM42,RBM43,RBM45,RBM46,RBM47,RBM48,RBM4B,RBM5,RBM6,RBM7,RBM8A,RBMS1,RBMS2,RBMS3,RBMS3-AS3,RBMX,RBMX2,RBMXL1,RBMXL2,RBMY1A1,RBMY1B,RBMY1D,RBMY1E,RBMY1F,RBMY1J,RBMY2AP,RBMY2BP,RBMY2DP,RBMY2FP,RBMY2TP,RBMY3AP,RBP1,RBP2,RBP3,RBP4,RBP5,RBP7,RBPJ,RBPJL,RBPMS,RBPMS-AS1,RBPMS2,RBSN,RBX1,RC3H1,RC3H2,RCAN1,RCAN2,RCAN3,RCBTB1,RCBTB2,RCC1,RCC1L,RCC2,RCCD1,RCE1,RCHY1,RCL1,RCN1,RCN2,RCN3,RCOR1,RCOR2,RCOR3,RCSD1,RCVRN,RD3,RDH10,RDH11,RDH12,RDH13,RDH14,RDH16,RDH5,RDH8,RDM1,RDX,REC114,REC8,RECK,RECQL,RECQL4,RECQL5,REDIC1,REEP1,REEP2,REEP3,REEP4,REEP5,REEP6,REG1A,REG1B,REG1CP,REG3A,REG3G,REG4,REL,RELA,RELB,RELCH,RELL1,RELL2,RELN,RELT,REM1,REM2,REN,RENBP,REPIN1,REPS1,REPS2,RER1,RERE,RERG,RERGL,RESF1,REST,RET,RETN,RETNLB,RETREG1,RETREG2,RETREG3,RETSAT,REV1,REV3L,REX1BD,REXO1,REXO1L1P,REXO2,REXO4,RFC1,RFC2,RFC3,RFC4,RFC5,RFESD,RFFL,RFK,RFLNA,RFLNB,RFNG,RFPL1,RFPL1S,RFPL2,RFPL3,RFPL3S,RFT1,RFTN1,RFTN2,RFWD3,RFX1,RFX2,RFX3,RFX4,RFX5,RFX6,RFX7,RFXANK,RFXAP,RGCC,RGL1,RGL2,RGL3,RGL4,RGMA,RGMB,RGMB-AS1,RGN,RGP1,RGPD1,RGPD2,RGPD3,RGPD4,RGPD4-AS1,RGPD5,RGPD6,RGPD8,RGR,RGS1,RGS10,RGS11,RGS12,RGS13,RGS14,RGS16,RGS17,RGS18,RGS19,RGS2,RGS20,RGS22,RGS3,RGS4,RGS5,RGS6,RGS7,RGS7BP,RGS8,RGS9,RGS9BP,RGSL1,RHAG,RHBDD1,RHBDD2,RHBDD3,RHBDF1,RHBDF2,RHBDL1,RHBDL2,RHBDL3,RHBG,RHCE,RHCG,RHD,RHEB,RHEBL1,RHEX,RHNO1,RHO,RHOA,RHOB,RHOBTB1,RHOBTB2,RHOBTB3,RHOC,RHOD,RHOF,RHOG,RHOH,RHOJ,RHOQ,RHOT1,RHOT2,RHOU,RHOV,RHOXF1,RHOXF2,RHOXF2B,RHPN1,RHPN1-AS1,RHPN2,RIBC1,RIBC2,RIC1,RIC3,RIC8A,RIC8B,RICTOR,RIDA,RIF1,RIGI,RIIAD1,RILP,RILPL1,RILPL2,RIMBP2,RIMBP3,RIMBP3B,RIMBP3C,RIMKLA,RIMKLB,RIMOC1,RIMS1,RIMS2,RIMS3,RIMS4,RIN1,RIN2,RIN3,RING1,RINT1,RIOK1,RIOK2,RIOK3,RIOX1,RIOX2,RIPK1,RIPK2,RIPK3,RIPK4,RIPOR1,RIPOR2,RIPOR3,RIPPLY1,RIPPLY2,RIPPLY3,RIT1,RIT2,RITA1,RLBP1,RLF,RLIG1,RLIM,RLN1,RLN2,RLN3,RMC1,RMDN1,RMDN2,RMDN3,RMI1,RMI2,RMND1,RMND5A,RMND5B,RMST,RN7SKP150,RNA45S5,RNASE1,RNASE11,RNASE2,RNASE2CP,RNASE3,RNASE4,RNASE6,RNASE7,RNASEH1,RNASEH2A,RNASEH2B,RNASEH2C,RNASEK,RNASEK-C17orf49,RNASEL,RNASET2,RND1,RND2,RND3,RNF10,RNF103,RNF11,RNF111,RNF112,RNF113A,RNF114,RNF115,RNF11P2,RNF121,RNF122,RNF123,RNF125,RNF126,RNF126P1,RNF128,RNF13,RNF130,RNF133,RNF135,RNF138,RNF139,RNF139-DT,RNF14,RNF141,RNF144A,RNF144B,RNF145,RNF146,RNF148,RNF149,RNF150,RNF151,RNF152,RNF157,RNF157-AS1,RNF166,RNF167,RNF168,RNF169,RNF17,RNF170,RNF175,RNF180,RNF181,RNF182,RNF183,RNF185,RNF185-AS1,RNF186,RNF187,RNF19A,RNF19B,RNF2,RNF20,RNF207,RNF208,RNF212,RNF212B,RNF213,RNF214,RNF215,RNF216,RNF217,RNF217-AS1,RNF220,RNF24,RNF25,RNF26,RNF31,RNF32,RNF32-DT,RNF34,RNF38,RNF39,RNF4,RNF40,RNF41,RNF43,RNF44,RNF5,RNF5P1,RNF6,RNF7,RNF8,RNFT1,RNFT2,RNGTT,RNH1,RNLS,RNMT,RNPC3,RNPEP,RNPEPL1,RNPS1,RNU2-22P,RO60,ROBO1,ROBO2,ROBO3,ROBO4,ROCK1,ROCK2,ROGDI,ROM1,ROMO1,ROPN1,ROPN1B,ROPN1L,ROR1,ROR1-AS1,ROR2,RORA,RORB,RORC,ROS1,RP1,RP1L1,RP2,RP9,RP9P,RPA1,RPA2,RPA3,RPA4,RPAIN,RPAP1,RPAP2,RPAP3,RPE,RPE65,RPEL1,RPF1,RPF2,RPGR,RPGRIP1,RPGRIP1L,RPH3A,RPH3AL,RPIA,RPL10,RPL10A,RPL10L,RPL11,RPL12,RPL13,RPL13A,RPL13AP17,RPL13AP5,RPL13AP6,RPL13P5,RPL14,RPL15,RPL17,RPL18,RPL18A,RPL18AP16,RPL18P10,RPL19,RPL21,RPL21P28,RPL22,RPL22L1,RPL22P22,RPL23,RPL23A,RPL23AP22,RPL23AP32,RPL23AP53,RPL23AP7,RPL24,RPL26L1,RPL26P37,RPL27,RPL27A,RPL27AP,RPL28,RPL29,RPL29P7,RPL3,RPL30,RPL31,RPL32,RPL32P3,RPL34,RPL34-DT,RPL35,RPL35A,RPL35P8,RPL36,RPL36A,RPL36AL,RPL37,RPL37A,RPL38,RPL39,RPL39L,RPL3L,RPL4,RPL41,RPL5,RPL6,RPL7,RPL7A,RPL7AP10,RPL7AP12,RPL7AP71,RPL7L1,RPL7P25,RPL7P27,RPL7P52,RPL8,RPL9,RPLP0,RPLP0P1,RPLP1,RPLP2,RPLP2P1,RPN1,RPN2,RPP14,RPP21,RPP25,RPP25L,RPP30,RPP38,RPP40,RPPH1,RPRD1A,RPRD1B,RPRD2,RPRM,RPRML,RPS10,RPS10P2,RPS10P5,RPS10P7,RPS11,RPS11P1,RPS11P6,RPS12,RPS13,RPS14,RPS15,RPS15A,RPS16,RPS16P5,RPS17,RPS17P5,RPS18,RPS19,RPS19BP1,RPS2,RPS20,RPS21,RPS23,RPS23P6,RPS24,RPS25,RPS26,RPS26P11,RPS27,RPS27A,RPS27L,RPS28,RPS29,RPS29P28,RPS2P45,RPS3,RPS3A,RPS4X,RPS4XP2,RPS4XP3,RPS4XP9,RPS4Y1,RPS5,RPS6,RPS6KA1,RPS6KA2,RPS6KA3,RPS6KA4,RPS6KA5,RPS6KA6,RPS6KB1,RPS6KB2,RPS6KC1,RPS6KL1,RPS7,RPS8,RPS9,RPSA,RPSA2,RPSAP19,RPSAP9,RPTN,RPTOR,RPUSD1,RPUSD2,RPUSD3,RPUSD4,RRAD,RRAGA,RRAGB,RRAGC,RRAGD,RRAS,RRAS2,RRBP1,RREB1,RRH,RRM1,RRM2,RRM2B,RRN3,RRN3P1,RRN3P2,RRN3P3,RRP1,RRP12,RRP15,RRP1B,RRP36,RRP7A,RRP7BP,RRP8,RRP9,RRS1,RRS1-DT,RS1,RSAD1,RSAD2,RSBN1,RSBN1L,RSC1A1,RSF1,RSKR,RSL1D1,RSL24D1,RSPH1,RSPH10B,RSPH10B2,RSPH14,RSPH3,RSPH4A,RSPH6A,RSPH9,RSPO1,RSPO2,RSPO3,RSPO4,RSPRY1,RSRC1,RSRC2,RSRP1,RSU1,RSU1P2,RTBDN,RTCA,RTCB,RTEL1,RTF1,RTF2,RTKN,RTKN2,RTL10,RTL3,RTL5,RTL6,RTL8A,RTL8C,RTL9,RTN1,RTN2,RTN3,RTN4,RTN4IP1,RTN4R,RTN4RL1,RTN4RL2,RTP1,RTP3,RTP4,RTP5,RTRAF,RTTN,RUBCN,RUBCNL,RUFY1,RUFY2,RUFY3,RUNDC1,RUNDC3A,RUNDC3B,RUNX1,RUNX1-IT1,RUNX1T1,RUNX2,RUNX3,RUSC1,RUSC1-AS1,RUSC2,RUSF1,RUVBL1,RUVBL2,RWDD1,RWDD2A,RWDD2B,RWDD3,RWDD4,RXFP1,RXFP2,RXFP3,RXRA,RXRB,RXRG,RXYLT1,RYBP,RYK,RYR1,RYR2,RYR3,S100A1,S100A10,S100A11,S100A11P1,S100A12,S100A13,S100A14,S100A16,S100A2,S100A3,S100A4,S100A5,S100A6,S100A7,S100A7A,S100A8,S100A9,S100B,S100G,S100P,S100PBP,S100Z,S1PR1,S1PR2,S1PR3,S1PR4,S1PR5,SAA1,SAA2,SAA2-SAA4,SAA3P,SAA4,SAAL1,SAC3D1,SACM1L,SACS,SACS-AS1,SAE1,SAFB,SAFB2,SAG,SAGE1,SALL1,SALL2,SALL3,SALL4,SAMD1,SAMD10,SAMD11,SAMD12,SAMD13,SAMD14,SAMD15,SAMD3,SAMD4A,SAMD4B,SAMD5,SAMD8,SAMD9,SAMD9L,SAMHD1,SAMM50,SAMSN1,SAMTOR,SANBR,SAP130,SAP18,SAP25,SAP30,SAP30BP,SAP30L,SAPCD1,SAPCD1-AS1,SAPCD2,SAR1A,SAR1B,SARAF,SARDH,SARM1,SARNP,SARS2,SART1,SART3,SASH1,SASH3,SASS6,SAT1,SAT2,SATB1,SATB2,SATB2-AS1,SAV1,SAXO1,SAXO2,SAXO4,SAXO5,SAYSD1,SBDS,SBDSP1,SBF1,SBF2,SBF2-AS1,SBK1,SBNO1,SBNO2,SBSN,SBSPON,SC5D,SCAF1,SCAF11,SCAF4,SCAF8,SCAI,SCAMP1,SCAMP1-AS1,SCAMP2,SCAMP3,SCAMP4,SCAMP5,SCAND1,SCAND2P,SCAND3,SCAP,SCAPER,SCARA3,SCARA5,SCARB1,SCARB2,SCARF1,SCARF2,SCARNA13,SCARNA15,SCARNA16,SCARNA17,SCARNA2,SCART1,SCCPDH,SCD,SCD5,SCEL,SCFD1,SCFD2,SCG2,SCG3,SCG5,SCGB1A1,SCGB1C1,SCGB1D1,SCGB1D2,SCGB2A1,SCGB2A2,SCGB2B2,SCGB3A1,SCGB3A2,SCGN,SCHIP1,SCIMP,SCIN,SCLT1,SCLY,SCMH1,SCML1,SCML2,SCML4,SCN10A,SCN11A,SCN1A,SCN1B,SCN2A,SCN2B,SCN3A,SCN3B,SCN4A,SCN4B,SCN5A,SCN7A,SCN8A,SCN9A,SCNM1,SCNN1A,SCNN1B,SCNN1D,SCNN1G,SCO1,SCO2,SCOC,SCOC-AS1,SCP2,SCP2D1,SCP2D1-AS1,SCPEP1,SCRG1,SCRIB,SCRN1,SCRN2,SCRN3,SCRT1,SCT,SCTR,SCUBE1,SCUBE2,SCUBE3,SCYL1,SCYL2,SCYL3,SDAD1,SDC1,SDC2,SDC3,SDC4,SDCBP,SDCBP2,SDCBP2-AS1,SDCCAG8,SDE2,SDF2,SDF2L1,SDF4,SDHA,SDHAF1,SDHAF2,SDHAF3,SDHAF4,SDHAP1,SDHAP2,SDHAP3,SDHB,SDHC,SDHD,SDK1,SDK2,SDR16C5,SDR39U1,SDR42E1,SDR9C7,SDS,SDSL,SEBOX,SEC11A,SEC11C,SEC13,SEC14L1,SEC14L1P1,SEC14L2,SEC14L3,SEC14L4,SEC14L5,SEC16A,SEC16B,SEC1P,SEC22A,SEC22B,SEC22C,SEC23A,SEC23B,SEC23IP,SEC24A,SEC24B,SEC24B-AS1,SEC24C,SEC24D,SEC31A,SEC31B,SEC61A1,SEC61A2,SEC61B,SEC61G,SEC62,SEC63,SECISBP2,SECISBP2L,SECTM1,SEH1L,SEL1L,SEL1L2,SEL1L3,SELE,SELENBP1,SELENOF,SELENOH,SELENOI,SELENOK,SELENOM,SELENON,SELENOO,SELENOP,SELENOS,SELENOT,SELENOW,SELL,SELP,SELPLG,SEM1,SEMA3A,SEMA3B,SEMA3C,SEMA3D,SEMA3E,SEMA3F,SEMA3G,SEMA4A,SEMA4B,SEMA4C,SEMA4D,SEMA4F,SEMA4G,SEMA5A,SEMA5B,SEMA6A,SEMA6B,SEMA6C,SEMA6D,SEMA7A,SEMG1,SEMG2,SENCR,SENP1,SENP2,SENP3,SENP5,SENP6,SENP7,SENP8,SEPHS1,SEPHS2,SEPSECS,SEPTIN1,SEPTIN10,SEPTIN11,SEPTIN12,SEPTIN3,SEPTIN4,SEPTIN5,SEPTIN6,SEPTIN7,SEPTIN7P2,SEPTIN7P9,SEPTIN8,SEPTIN9,SERAC1,SERBP1,SERF1A,SERF1B,SERF2,SERF2-C15ORF63,SERGEF,SERHL,SERHL2,SERINC1,SERINC2,SERINC3,SERINC5,SERP1,SERP2,SERPINA1,SERPINA10,SERPINA12,SERPINA2,SERPINA3,SERPINA4,SERPINA5,SERPINA6,SERPINA7,SERPINA9,SERPINB1,SERPINB10,SERPINB11,SERPINB12,SERPINB13,SERPINB2,SERPINB3,SERPINB4,SERPINB5,SERPINB6,SERPINB7,SERPINB8,SERPINB9,SERPINB9P1,SERPINC1,SERPIND1,SERPINE1,SERPINE2,SERPINF1,SERPINF2,SERPING1,SERPINH1,SERPINI1,SERPINI2,SERTAD1,SERTAD2,SERTAD3,SERTAD4,SERTM1,SESN1,SESN2,SESN3,SESTD1,SET,SETBP1,SETD1A,SETD1B,SETD2,SETD3,SETD4,SETD5,SETD6,SETD7,SETD9,SETDB1,SETDB2,SETMAR,SETP4,SETSIP,SETX,SEZ6,SEZ6L,SEZ6L2,SF1,SF3A1,SF3A2,SF3A3,SF3B1,SF3B2,SF3B3,SF3B4,SF3B5,SF3B6,SFI1,SFMBT1,SFMBT2,SFN,SFPQ,SFR1,SFRP1,SFRP2,SFRP4,SFRP5,SFSWAP,SFT2D1,SFT2D2,SFT2D3,SFTA1P,SFTA2,SFTA3,SFTPA1,SFTPA2,SFTPB,SFTPC,SFTPD,SFXN1,SFXN2,SFXN3,SFXN4,SFXN5,SGCA,SGCB,SGCD,SGCE,SGCG,SGCZ,SGF29,SGIP1,SGK1,SGK2,SGK3,SGMS1,SGMS2,SGO1,SGO2,SGPL1,SGPP1,SGPP2,SGSH,SGSM1,SGSM2,SGSM3,SGTA,SGTB,SH2B1,SH2B2,SH2B3,SH2D1A,SH2D1B,SH2D2A,SH2D3A,SH2D3C,SH2D4A,SH2D4B,SH2D5,SH2D6,SH3BGR,SH3BGRL,SH3BGRL2,SH3BGRL3,SH3BP1,SH3BP2,SH3BP4,SH3BP5,SH3BP5-AS1,SH3BP5L,SH3D19,SH3D21,SH3GL1,SH3GL1P1,SH3GL1P2,SH3GL2,SH3GL3,SH3GLB1,SH3GLB2,SH3KBP1,SH3PXD2A,SH3PXD2B,SH3RF1,SH3RF2,SH3RF3,SH3RF3-AS1,SH3TC1,SH3TC2,SH3YL1,SHANK1,SHANK2,SHANK2-AS2,SHANK2-AS3,SHANK3,SHARPIN,SHB,SHBG,SHC1,SHC1P1,SHC2,SHC3,SHC4,SHCBP1,SHCBP1L,SHD,SHE,SHF,SHFL,SHH,SHISA2,SHISA3,SHISA4,SHISA5,SHISA6,SHISA7,SHISA8,SHISA9,SHISAL1,SHISAL2A,SHKBP1,SHLD1,SHLD2,SHMT1,SHMT2,SHOC1,SHOC2,SHOX,SHOX2,SHPK,SHPRH,SHQ1,SHROOM1,SHROOM2,SHROOM3,SHROOM4,SHTN1,SI,SIAE,SIAH1,SIAH2,SIAH3,SIDT1,SIDT2,SIGIRR,SIGLEC1,SIGLEC10,SIGLEC11,SIGLEC15,SIGLEC16,SIGLEC17P,SIGLEC5,SIGLEC6,SIGLEC7,SIGLEC8,SIGLEC9,SIGLECL1,SIGMAR1,SIK1,SIK2,SIK3,SIKE1,SIL1,SIM1,SIM2,SIMC1,SIN3A,SIN3B,SINHCAF,SIPA1,SIPA1L1,SIPA1L2,SIPA1L3,SIRPA,SIRPAP1,SIRPB1,SIRPB2,SIRPD,SIRPG,SIRT1,SIRT2,SIRT3,SIRT4,SIRT5,SIRT6,SIRT7,SIT1,SIVA1,SIX1,SIX2,SIX3,SIX3-AS1,SIX4,SIX5,SIX6,SKA1,SKA2,SKA3,SKAP1,SKAP2,SKI,SKIC2,SKIC3,SKIC8,SKIDA1,SKIL,SKP1,SKP2,SLA,SLA2,SLAIN1,SLAIN2,SLAMF1,SLAMF6,SLAMF7,SLAMF8,SLAMF9,SLBP,SLC10A1,SLC10A2,SLC10A3,SLC10A4,SLC10A7,SLC11A1,SLC11A2,SLC12A1,SLC12A2,SLC12A3,SLC12A4,SLC12A5,SLC12A6,SLC12A7,SLC12A8,SLC12A9,SLC13A1,SLC13A2,SLC13A3,SLC13A4,SLC13A5,SLC14A1,SLC14A2,SLC15A1,SLC15A2,SLC15A3,SLC15A4,SLC16A1,SLC16A10,SLC16A11,SLC16A14,SLC16A2,SLC16A3,SLC16A4,SLC16A5,SLC16A6,SLC16A7,SLC16A8,SLC16A9,SLC17A1,SLC17A2,SLC17A3,SLC17A4,SLC17A5,SLC17A6,SLC17A7,SLC17A8,SLC17A9,SLC18A1,SLC18A2,SLC18A3,SLC18B1,SLC19A1,SLC19A2,SLC19A3,SLC19A4P,SLC1A1,SLC1A2,SLC1A3,SLC1A4,SLC1A5,SLC1A6,SLC1A7,SLC20A1,SLC20A2,SLC22A1,SLC22A11,SLC22A12,SLC22A13,SLC22A14,SLC22A15,SLC22A16,SLC22A17,SLC22A18,SLC22A18AS,SLC22A2,SLC22A23,SLC22A24,SLC22A25,SLC22A3,SLC22A31,SLC22A4,SLC22A5,SLC22A6,SLC22A7,SLC22A8,SLC22A9,SLC23A1,SLC23A2,SLC23A3,SLC24A1,SLC24A2,SLC24A3,SLC24A4,SLC24A5,SLC25A1,SLC25A10,SLC25A11,SLC25A12,SLC25A13,SLC25A14,SLC25A15,SLC25A16,SLC25A17,SLC25A18,SLC25A19,SLC25A2,SLC25A20,SLC25A21,SLC25A22,SLC25A23,SLC25A24,SLC25A25,SLC25A26,SLC25A27,SLC25A28,SLC25A29,SLC25A3,SLC25A30,SLC25A31,SLC25A32,SLC25A33,SLC25A34,SLC25A35,SLC25A36,SLC25A37,SLC25A38,SLC25A39,SLC25A3P1,SLC25A4,SLC25A40,SLC25A41,SLC25A42,SLC25A43,SLC25A44,SLC25A45,SLC25A46,SLC25A47,SLC25A48,SLC25A5,SLC25A51,SLC25A53,SLC25A6,SLC26A1,SLC26A10P,SLC26A11,SLC26A2,SLC26A3,SLC26A4,SLC26A6,SLC26A7,SLC26A8,SLC26A9,SLC27A1,SLC27A2,SLC27A3,SLC27A4,SLC27A5,SLC27A6,SLC28A1,SLC28A2,SLC28A3,SLC29A1,SLC29A2,SLC29A3,SLC29A4,SLC2A1,SLC2A1-DT,SLC2A10,SLC2A11,SLC2A12,SLC2A13,SLC2A14,SLC2A2,SLC2A3,SLC2A4,SLC2A4RG,SLC2A5,SLC2A6,SLC2A8,SLC2A9,SLC30A1,SLC30A10,SLC30A2,SLC30A3,SLC30A4,SLC30A5,SLC30A6,SLC30A7,SLC30A8,SLC30A9,SLC31A1,SLC31A2,SLC32A1,SLC33A1,SLC34A1,SLC34A2,SLC34A3,SLC35A1,SLC35A2,SLC35A3,SLC35A4,SLC35A5,SLC35B1,SLC35B2,SLC35B3,SLC35B4,SLC35C1,SLC35C2,SLC35D1,SLC35D2,SLC35D3,SLC35E1,SLC35E2B,SLC35E3,SLC35E4,SLC35F1,SLC35F2,SLC35F3,SLC35F4,SLC35F5,SLC35F6,SLC35G1,SLC35G2,SLC35G3,SLC35G4,SLC35G5,SLC36A1,SLC36A4,SLC37A1,SLC37A2,SLC37A3,SLC37A4,SLC38A1,SLC38A10,SLC38A11,SLC38A2,SLC38A3,SLC38A4,SLC38A5,SLC38A6,SLC38A7,SLC38A9,SLC39A1,SLC39A10,SLC39A11,SLC39A12,SLC39A13,SLC39A14,SLC39A2,SLC39A3,SLC39A4,SLC39A5,SLC39A6,SLC39A7,SLC39A8,SLC39A9,SLC3A1,SLC3A2,SLC40A1,SLC41A1,SLC41A2,SLC41A3,SLC43A1,SLC43A2,SLC43A3,SLC44A1,SLC44A2,SLC44A3,SLC44A4,SLC44A5,SLC45A1,SLC45A2,SLC45A3,SLC45A4,SLC46A1,SLC46A2,SLC46A3,SLC47A1,SLC47A2,SLC48A1,SLC49A3,SLC49A4,SLC4A1,SLC4A10,SLC4A11,SLC4A1AP,SLC4A2,SLC4A3,SLC4A4,SLC4A5,SLC4A7,SLC4A8,SLC4A9,SLC50A1,SLC51A,SLC51B,SLC52A1,SLC52A2,SLC52A3,SLC5A1,SLC5A10,SLC5A11,SLC5A12,SLC5A2,SLC5A3,SLC5A4,SLC5A5,SLC5A6,SLC5A7,SLC5A8,SLC5A9,SLC66A1,SLC66A1LP,SLC66A2,SLC66A3,SLC6A1,SLC6A10P,SLC6A10PB,SLC6A11,SLC6A12,SLC6A13,SLC6A14,SLC6A15,SLC6A16,SLC6A17,SLC6A18,SLC6A19,SLC6A2,SLC6A20,SLC6A3,SLC6A4,SLC6A5,SLC6A6,SLC6A7,SLC6A8,SLC6A9,SLC7A1,SLC7A10,SLC7A11,SLC7A13,SLC7A14,SLC7A2,SLC7A3,SLC7A4,SLC7A5,SLC7A5P1,SLC7A5P2,SLC7A6,SLC7A6OS,SLC7A7,SLC7A8,SLC7A9,SLC8A1,SLC8A1-AS1,SLC8A2,SLC8A3,SLC8B1,SLC9A1,SLC9A2,SLC9A3,SLC9A3-OT1,SLC9A5,SLC9A6,SLC9A7,SLC9A8,SLC9A9,SLC9B1,SLC9B2,SLC9C2,SLCO1A2,SLCO1B1,SLCO1B3,SLCO1C1,SLCO2A1,SLCO2B1,SLCO3A1,SLCO4A1,SLCO4C1,SLCO5A1,SLCO6A1,SLF1,SLF2,SLFN11,SLFN12,SLFN13,SLFN5,SLFNL1,SLFNL1-AS1,SLIRP,SLIRP-OT1,SLIT1,SLIT2,SLIT2-IT1,SLIT3,SLITRK1,SLITRK2,SLITRK3,SLITRK4,SLITRK5,SLITRK6,SLK,SLMAP,SLN,SLPI,SLTM,SLU7,SLURP1,SLX1A,SLX1B,SLX4,SLX4IP,SLX9,SMAD1,SMAD1-AS2,SMAD2,SMAD3,SMAD4,SMAD5,SMAD5-AS1,SMAD6,SMAD7,SMAD9,SMAGP,SMAP1,SMAP2,SMARCA1,SMARCA2,SMARCA4,SMARCA5,SMARCAD1,SMARCAL1,SMARCB1,SMARCC1,SMARCC2,SMARCD1,SMARCD2,SMARCD3,SMARCE1,SMARCE1P2,SMC1A,SMC1B,SMC2,SMC3,SMC4,SMC5,SMC5-DT,SMC6,SMCHD1,SMCO1,SMCO3,SMCO4,SMCP,SMCR5,SMCR8,SMDT1,SMG1,SMG1P1,SMG1P2,SMG1P3,SMG1P5,SMG1P7,SMG5,SMG6,SMG7,SMG7-AS1,SMG8,SMG9,SMIM1,SMIM10,SMIM11,SMIM12,SMIM13,SMIM14,SMIM15,SMIM17,SMIM19,SMIM2,SMIM2-AS1,SMIM20,SMIM21,SMIM22,SMIM24,SMIM27,SMIM29,SMIM3,SMIM43,SMIM5,SMIM7,SMIM8,SMKR1,SMLR1,SMN1,SMN2,SMNDC1,SMO,SMOC1,SMOC2,SMOX,SMPD1,SMPD2,SMPD3,SMPD4,SMPDL3A,SMPDL3B,SMPX,SMR3A,SMR3B,SMS,SMTN,SMTNL1,SMTNL2,SMU1,SMUG1,SMURF1,SMURF2,SMYD1,SMYD2,SMYD3,SMYD4,SMYD5,SNAI1,SNAI1P1,SNAI2,SNAI3,SNAI3-AS1,SNAP23,SNAP25,SNAP29,SNAP47,SNAP91,SNAPC1,SNAPC2,SNAPC3,SNAPC4,SNAPC5,SNAPIN,SNCA,SNCAIP,SNCB,SNCG,SND1,SND1-IT1,SNED1,SNF8,SNHG1,SNHG10,SNHG11,SNHG12,SNHG15,SNHG16,SNHG17,SNHG18,SNHG19,SNHG20,SNHG22,SNHG28,SNHG3,SNHG32,SNHG4,SNHG5,SNHG6,SNHG7,SNHG8,SNHG9,SNIP1,SNN,SNORA1,SNORA11D,SNORA11E,SNORA16A,SNORA17A,SNORA17B,SNORA18,SNORA21,SNORA24,SNORA27,SNORA28,SNORA29,SNORA32,SNORA37,SNORA3A,SNORA4,SNORA40,SNORA41,SNORA44,SNORA48,SNORA50C,SNORA52,SNORA56,SNORA57,SNORA5B,SNORA6,SNORA60,SNORA61,SNORA62,SNORA63,SNORA64,SNORA65,SNORA66,SNORA67,SNORA68,SNORA70,SNORA71A,SNORA71B,SNORA71E,SNORA72,SNORA73A,SNORA74A,SNORA78,SNORA8,SNORA81,SNORA9,SNORC,SNORD10,SNORD102,SNORD104,SNORD107,SNORD110,SNORD112,SNORD114-3,SNORD115-7,SNORD116-4,SNORD139,SNORD14B,SNORD14C,SNORD14D,SNORD16,SNORD18A,SNORD18B,SNORD18C,SNORD19B,SNORD1A,SNORD1C,SNORD2,SNORD21,SNORD22,SNORD23,SNORD24,SNORD25,SNORD26,SNORD27,SNORD28,SNORD29,SNORD30,SNORD31,SNORD32A,SNORD33,SNORD34,SNORD35A,SNORD35B,SNORD36A,SNORD36B,SNORD38B,SNORD3A,SNORD3B-1,SNORD3B-2,SNORD3C,SNORD3D,SNORD42A,SNORD44,SNORD45A,SNORD45B,SNORD45C,SNORD47,SNORD49A,SNORD49B,SNORD4A,SNORD5,SNORD50A,SNORD50B,SNORD54,SNORD55,SNORD57,SNORD58A,SNORD58B,SNORD58C,SNORD61,SNORD65,SNORD68,SNORD73A,SNORD74,SNORD76,SNORD77,SNORD79,SNORD8,SNORD80,SNORD81,SNORD83B,SNORD84,SNORD86,SNORD87,SNORD88C,SNORD89,SNORD95,SNORD96A,SNPH,SNRK,SNRK-AS1,SNRNP200,SNRNP25,SNRNP27,SNRNP35,SNRNP40,SNRNP48,SNRNP70,SNRPA,SNRPA1,SNRPB,SNRPB2,SNRPC,SNRPD1,SNRPD2,SNRPD3,SNRPE,SNRPF,SNRPG,SNRPN,SNTA1,SNTB1,SNTB2,SNTG1,SNTG2,SNTN,SNU13,SNUPN,SNURF,SNW1,SNX1,SNX10,SNX11,SNX12,SNX13,SNX14,SNX15,SNX16,SNX17,SNX18,SNX18P3,SNX19,SNX2,SNX20,SNX21,SNX22,SNX24,SNX25,SNX27,SNX29,SNX29P1,SNX29P2,SNX3,SNX30,SNX31,SNX32,SNX33,SNX4,SNX5,SNX6,SNX7,SNX8,SNX9,SOAT1,SOAT2,SOBP,SOCS1,SOCS2,SOCS2-AS1,SOCS3,SOCS4,SOCS5,SOCS6,SOCS7,SOD1,SOD2,SOD3,SOHLH1,SOHLH2,SON,SORBS1,SORBS2,SORBS3,SORCS1,SORCS2,SORCS3,SORCS3-AS1,SORD,SORL1,SORT1,SOS1,SOS1-IT1,SOS2,SOST,SOSTDC1,SOWAHA,SOWAHC,SOX1,SOX10,SOX11,SOX12,SOX13,SOX14,SOX15,SOX17,SOX18,SOX2,SOX2-OT,SOX21,SOX21-AS1,SOX3,SOX30,SOX4,SOX5,SOX5P1,SOX6,SOX7,SOX8,SOX9,SOX9-AS1,SP1,SP100,SP110,SP140,SP140L,SP2,SP3,SP3P,SP4,SP5,SP6,SP7,SP8,SPA17,SPACA1,SPACA3,SPACA4,SPACA6,SPACA7,SPACA9,SPACDR,SPAG1,SPAG11A,SPAG11B,SPAG16,SPAG17,SPAG4,SPAG5,SPAG5-AS1,SPAG6,SPAG7,SPAG8,SPAG9,SPAM1,SPANXA1,SPANXA2,SPANXB1,SPANXC,SPARC,SPARCL1,SPART,SPART-AS1,SPAST,SPATA1,SPATA12,SPATA13,SPATA16,SPATA17,SPATA18,SPATA19,SPATA2,SPATA20,SPATA21,SPATA22,SPATA24,SPATA25,SPATA2L,SPATA3,SPATA3-AS1,SPATA31A1,SPATA31A3,SPATA31A5,SPATA31A6,SPATA31A7,SPATA31C2,SPATA31D1,SPATA31D3,SPATA31D4,SPATA31E1,SPATA31F1,SPATA31F2P,SPATA31F3,SPATA31G1,SPATA31H1,SPATA32,SPATA33,SPATA4,SPATA41,SPATA42,SPATA45,SPATA46,SPATA6,SPATA6L,SPATA7,SPATA8,SPATA9,SPATC1,SPATC1L,SPATS1,SPATS2,SPATS2L,SPC24,SPC25,SPCS1,SPCS2,SPCS3,SPDEF,SPDL1,SPDYA,SPDYE1,SPDYE2,SPDYE2B,SPDYE5,SPDYE6,SPECC1,SPECC1L,SPEF1,SPEF2,SPEG,SPEM1,SPEM2,SPEN,SPESP1,SPG11,SPG21,SPG7,SPHK1,SPHK2,SPHKAP,SPI1,SPIB,SPIC,SPICE1,SPIDR,SPIN1,SPIN2A,SPIN2B,SPIN3,SPIN4,SPINDOC,SPINK1,SPINK13,SPINK2,SPINK4,SPINK5,SPINK6,SPINK7,SPINT1,SPINT2,SPINT3,SPIRE1,SPIRE2,SPMAP1,SPMAP2,SPMIP10,SPMIP2,SPMIP3,SPMIP4,SPMIP5,SPMIP6,SPMIP8,SPMIP9,SPN,SPNS1,SPNS2,SPNS3,SPO11,SPOCD1,SPOCK1,SPOCK2,SPOCK3,SPON1,SPON2,SPOP,SPOPL,SPOUT1,SPP1,SPP2,SPPL2A,SPPL2B,SPPL2C,SPPL3,SPR,SPRED1,SPRED2,SPRED3,SPRING1,SPRN,SPRNP1,SPRR1A,SPRR1B,SPRR2B,SPRR2C,SPRR2G,SPRR3,SPRR4,SPRTN,SPRY1,SPRY2,SPRY3,SPRY4,SPRY4-IT1,SPRYD3,SPRYD4,SPRYD7,SPSB1,SPSB2,SPSB3,SPSB4,SPTA1,SPTAN1,SPTB,SPTBN1,SPTBN2,SPTBN4,SPTBN5,SPTLC1,SPTLC2,SPTLC3,SPTSSA,SPTSSB,SPTY2D1,SPX,SPZ1,SQLE,SQOR,SQSTM1,SRA1,SRARP,SRBD1,SRC,SRCAP,SRCIN1,SRD5A1,SRD5A2,SRD5A3,SRD5A3-AS1,SREBF1,SREBF2,SREK1,SREK1IP1,SRF,SRFBP1,SRGAP1,SRGAP2,SRGAP2B,SRGAP2C,SRGAP3,SRGN,SRI,SRL,SRM,SRMP1,SRMS,SRP14,SRP19,SRP54,SRP68,SRP72,SRP9,SRPK1,SRPK2,SRPK3,SRPRA,SRPRB,SRPX,SRPX2,SRR,SRRD,SRRM1,SRRM2,SRRM2-AS1,SRRM3,SRRM4,SRRM5,SRRT,SRSF1,SRSF10,SRSF11,SRSF12,SRSF2,SRSF3,SRSF4,SRSF5,SRSF6,SRSF7,SRSF8,SRSF9,SRXN1,SRY,SS18,SS18L1,SS18L2,SSB,SSBP1,SSBP2,SSBP3,SSBP3-AS1,SSBP4,SSC4D,SSC5D,SSH1,SSH2,SSH3,SSMEM1,SSNA1,SSPN,SSPOP,SSR1,SSR2,SSR3,SSR4,SSR4P1,SSRP1,SST,SSTR1,SSTR2,SSTR3,SSTR4,SSTR5,SSTR5-AS1,SSU72,SSU72L6,SSUH2,SSX1,SSX2,SSX2B,SSX2IP,SSX3,SSX4,SSX4B,SSX5,SSX7,ST13,ST14,ST18,ST20,ST20-AS1,ST20-MTHFS,ST3GAL1,ST3GAL2,ST3GAL3,ST3GAL4,ST3GAL5,ST3GAL6,ST6GAL1,ST6GAL2,ST6GALNAC1,ST6GALNAC2,ST6GALNAC3,ST6GALNAC4,ST6GALNAC5,ST6GALNAC6,ST7,ST7-AS1,ST7-AS2,ST7-OT3,ST7-OT4,ST7L,ST8SIA1,ST8SIA2,ST8SIA3,ST8SIA4,ST8SIA5,STAB1,STAB2,STAC,STAC2,STAC3,STAG1,STAG2,STAG3,STAG3L1,STAG3L2,STAG3L3,STAG3L4,STAM,STAM-DT,STAM2,STAMBP,STAMBPL1,STAP1,STAP2,STAR,STARD10,STARD13,STARD13-AS,STARD3,STARD3NL,STARD4,STARD5,STARD6,STARD7,STARD7-AS1,STARD8,STARD9,STAT1,STAT2,STAT3,STAT4,STAT5A,STAT5B,STAT6,STATH,STAU1,STAU2,STAU2-AS1,STBD1,STC1,STC2,STEAP1,STEAP1B,STEAP2,STEAP3,STEAP4,STH,STIL,STIM1,STIM2,STIMATE,STING1,STIP1,STK10,STK11,STK11IP,STK16,STK17A,STK17B,STK24,STK24-AS1,STK25,STK26,STK3,STK31,STK32A,STK32B,STK32C,STK33,STK35,STK36,STK38,STK38L,STK39,STK4,STK4-DT,STK40,STKLD1,STMN1,STMN2,STMN3,STMN4,STMP1,STN1,STOM,STOML1,STOML2,STOML3,STON1,STON2,STOX1,STOX2,STPG1,STPG2,STPG3,STPG4,STRA6,STRADA,STRADB,STRAP,STRBP,STRC,STRIP1,STRIP2,STRN,STRN3,STRN4,STS,STT3A,STT3B,STUB1,STUM,STX10,STX11,STX12,STX16,STX17,STX18,STX18-AS1,STX19,STX1A,STX1B,STX2,STX3,STX4,STX5,STX6,STX7,STX8,STXBP1,STXBP2,STXBP3,STXBP4,STXBP5,STXBP5-AS1,STXBP5L,STXBP6,STYK1,STYX,STYXL1,SUB1,SUCLA2,SUCLG1,SUCLG2,SUCLG2-DT,SUCNR1,SUCO,SUDS3,SUFU,SUGCT,SUGP1,SUGP2,SUGT1,SUGT1P1,SUGT1P3,SULF1,SULF2,SULT1A1,SULT1A2,SULT1A3,SULT1A4,SULT1B1,SULT1C2,SULT1C4,SULT1E1,SULT2A1,SULT2B1,SULT4A1,SUMF1,SUMF2,SUMO1,SUMO1P2,SUMO2,SUMO3,SUMO4,SUN1,SUN2,SUN3,SUN5,SUOX,SUPT16H,SUPT20H,SUPT3H,SUPT4H1,SUPT5H,SUPT6H,SUPT7L,SUPV3L1,SURF1,SURF2,SURF4,SURF6,SUSD1,SUSD2,SUSD3,SUSD4,SUSD5,SUSD6,SUV39H1,SUV39H2,SUZ12,SUZ12P1,SV2A,SV2B,SV2C,SVBP,SVEP1,SVIL,SVIP,SVOP,SVOPL,SWAP70,SWI5,SWSAP1,SWT1,SYAP1,SYBU,SYCE1,SYCE1L,SYCE2,SYCE3,SYCN,SYCP1,SYCP2,SYCP2L,SYCP3,SYDE1,SYDE2,SYF2,SYK,SYMPK,SYN1,SYN2,SYN3,SYNC,SYNCRIP,SYNDIG1,SYNDIG1L,SYNE1,SYNE2,SYNE3,SYNE4,SYNGAP1,SYNGR1,SYNGR2,SYNGR3,SYNGR4,SYNJ1,SYNJ2,SYNJ2BP,SYNM,SYNPO,SYNPO2,SYNPO2L,SYNPR,SYNPR-AS1,SYNRG,SYP,SYPL1,SYPL2,SYS1,SYT1,SYT11,SYT12,SYT13,SYT14,SYT15,SYT16,SYT17,SYT2,SYT3,SYT4,SYT5,SYT6,SYT7,SYT8,SYT9,SYTL1,SYTL2,SYTL3,SYTL4,SYTL5,SYVN1,SZRD1,SZT2,TAAR1,TAAR2,TAAR3P,TAAR5,TAAR8,TAAR9,TAB1,TAB2,TAB3,TAC1,TAC3,TAC4,TACC1,TACC2,TACC3,TACO1,TACR1,TACR2,TACR3,TACSTD2,TADA1,TADA2A,TADA2B,TADA3,TAF1,TAF10,TAF11,TAF12,TAF13,TAF15,TAF1A,TAF1A-AS1,TAF1B,TAF1C,TAF1D,TAF1L,TAF2,TAF3,TAF4,TAF4B,TAF5,TAF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diff --git a/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE117613.csv b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE117613.csv new file mode 100644 index 0000000000000000000000000000000000000000..05628bc952a49cc412f1e1e98af5b1fd47bfbdb2 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE117613.csv @@ -0,0 +1,4 @@ +,GSM3305150,GSM3305151,GSM3305152,GSM3305153,GSM3305154,GSM3305155,GSM3305156,GSM3305157,GSM3305158,GSM3305159,GSM3305160,GSM3305161,GSM3305162,GSM3305163,GSM3305164,GSM3305165,GSM3305166,GSM3305167,GSM3305168,GSM3305169,GSM3305170,GSM3305171,GSM3305172,GSM3305173,GSM3305174,GSM3305175,GSM3305176,GSM3305177,GSM3305178,GSM3305179,GSM3305180,GSM3305181,GSM3305182,GSM3305183,GSM3305184,GSM3305185,GSM3305186,GSM3305187,GSM3305188,GSM3305189,GSM3305190,GSM3305191,GSM3305192,GSM3305193,GSM3305194,GSM3305195 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-0,0 +1,2 @@ +,GSM1293592,GSM1293593,GSM1293594,GSM1293595,GSM1293596,GSM1293597,GSM1293598,GSM1293599,GSM1293600,GSM1293601,GSM1293602,GSM1293603,GSM1293604,GSM1293605,GSM1293606,GSM1293607,GSM1293608,GSM1293609,GSM1293610,GSM1293611,GSM1293612,GSM1293613,GSM1293614,GSM1293615,GSM1293616,GSM1293617,GSM1293618,GSM1293619,GSM1293620,GSM1293621,GSM1293622,GSM1293623,GSM1293624,GSM1293625 +Sickle_Cell_Anemia,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 diff --git a/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84632.csv b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84632.csv new file mode 100644 index 0000000000000000000000000000000000000000..143c52892d77fe3a6f12490044dda2bd61ad1ece --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84632.csv @@ -0,0 +1,2 @@ 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+Sickle_Cell_Anemia,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 diff --git a/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84633.csv b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84633.csv new file mode 100644 index 0000000000000000000000000000000000000000..7e49bdaf645bd7de985ee8946a1837d5d578660f --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84633.csv @@ -0,0 +1,2 @@ +,GSM2243302,GSM2243303,GSM2243304,GSM2243305,GSM2243306,GSM2243307,GSM2243308,GSM2243309,GSM2243310,GSM2243311,GSM2243312,GSM2243313,GSM2243314,GSM2243315,GSM2243316,GSM2243317,GSM2243318,GSM2243319,GSM2243320,GSM2243321,GSM2243322,GSM2243323,GSM2243324,GSM2243325,GSM2243326,GSM2243327,GSM2243328,GSM2243329,GSM2243330,GSM2243331,GSM2243332,GSM2243333,GSM2243334,GSM2243335,GSM2243336,GSM2243337,GSM2243338,GSM2243339,GSM2243340,GSM2243341 +Sickle_Cell_Anemia,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 diff --git a/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84634.csv b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84634.csv new file mode 100644 index 0000000000000000000000000000000000000000..9c2d3450ef6015856f1233c971f26270f0e8cf1a --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/clinical_data/GSE84634.csv @@ -0,0 +1,2 @@ +,GSM2243346,GSM2243347,GSM2243348,GSM2243349,GSM2243350,GSM2243351,GSM2243352,GSM2243353,GSM2243354,GSM2243355,GSM2243356,GSM2243357,GSM2243358,GSM2243359,GSM2243360,GSM2243361,GSM2243362,GSM2243363,GSM2243364,GSM2243365,GSM2243366,GSM2243367,GSM2243368,GSM2243369,GSM2243370,GSM2243371,GSM2243372,GSM2243373,GSM2243374,GSM2243375,GSM2243376,GSM2243377,GSM2243378,GSM2243379,GSM2243380,GSM2243381,GSM2243382,GSM2243383 +Sickle_Cell_Anemia,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0 diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE117613.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE117613.py new file mode 100644 index 0000000000000000000000000000000000000000..3c665e95197fef99d0d3f3e779d4e154d9b9a72f --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE117613.py @@ -0,0 +1,178 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE117613" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE117613" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE117613.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE117613.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE117613.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# From background info, we see the study used "Illumina HumanHT-12 v4 Expression BeadChip" +# This indicates gene expression data is available +is_gene_available = True + +# 2. Variable Availability and Data Type Conversion +# 2.1 Find key numbers for variables +# Diagnosis status in row 0 indicates trait info +trait_row = 0 + +# Age info in row 2 +age_row = 2 + +# Sex/gender info in row 4 +gender_row = 4 + +# 2.2 Data Type Conversion Functions +def convert_trait(value: str) -> int: + """Convert diagnosis status to binary trait indicator.""" + if not value or 'diagnosis:' not in value: + return None + value = value.lower().split('diagnosis:')[1].strip() + # From background, we know this is a malaria study. Control group has no infection. + if 'no plasmodium falciparum infection' in value: + return 0 + elif 'severe malaral anemia' in value or 'cerebral milaria' in value: + return 1 + return None + +def convert_age(value: str) -> float: + """Convert age string to float years.""" + if not value or 'age:' not in value: + return None + try: + return float(value.split('age:')[1].strip()) + except: + return None + +def convert_gender(value: str) -> int: + """Convert sex/gender string to binary (0=female, 1=male).""" + if not value or 'Sex:' not in value: + return None + value = value.lower().split('sex:')[1].strip() + if value == 'female': + return 0 + elif value == 'male': + return 1 + return None + +# 3. Save initial metadata +validate_and_save_cohort_info( + is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=(trait_row is not None) +) + +# 4. Extract clinical features if available +if trait_row is not None: + clinical_features = geo_select_clinical_features( + clinical_df=clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender + ) + + # Preview the data + print("Preview of clinical features:") + print(preview_df(clinical_features)) + + # Save to CSV + clinical_features.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# The IDs start with "ILMN_" which indicates these are Illumina probe IDs +# These need to be mapped to human gene symbols for analysis +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# Get mapping dataframe with probe IDs and gene symbols +mapping_data = get_gene_mapping(gene_annotation, prob_col='ID', gene_col='Symbol') + +# Convert probe-level data to gene-level expression data +gene_data = apply_gene_mapping(genetic_data, mapping_data) + +# Save gene expression data +gene_data.to_csv(out_gene_data_file) +# 1. Normalize gene symbols in gene expression data +gene_data = normalize_gene_symbols_in_index(gene_data) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +print("\nGene data shape (normalized gene-level):", gene_data.shape) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data using normalized gene-level data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, gene_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE41575.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE41575.py new file mode 100644 index 0000000000000000000000000000000000000000..beb135e01403ad4950765db0cdc7354596365211 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE41575.py @@ -0,0 +1,66 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE41575" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE41575" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE41575.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE41575.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE41575.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# This is microRNA data, not gene expression data +is_gene_available = False + +# 2.1 Data Availability +# No trait status data - only control vs miR overexpression +trait_row = None + +# No age data available +age_row = None + +# No gender data available +gender_row = None + +# 2.2 Data Type Conversion Functions +def convert_trait(x): + # Not needed since trait data not available + return None + +def convert_age(x): + # Not needed since age data not available + return None + +def convert_gender(x): + # Not needed since gender data not available + return None + +# 3. Save metadata +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=False) + +# 4. Skip clinical feature extraction since trait_row is None \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE46471.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE46471.py new file mode 100644 index 0000000000000000000000000000000000000000..6067cf91fdc5604b126329ed19b94b14dc29da73 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE46471.py @@ -0,0 +1,130 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE46471" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE46471" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE46471.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE46471.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE46471.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# Yes, this is a microarray gene expression dataset studying endothelial cells +is_gene_available = True + +# 2. Variable Availability and Data Type Conversion +# 2.1 Data Availability +# For this specific dataset studying damage pathways in endothelial cells, +# all samples are control samples (no disease state), so trait data is not available +trait_row = None + +# No age data available in sample characteristics +age_row = None + +# No gender data available in sample characteristics +gender_row = None + +# 2.2 Data Type Conversion +def convert_trait(x): + # Not needed since trait data is not available + return None + +def convert_age(x): + # Not needed since age data is not available + return None + +def convert_gender(x): + # Not needed since gender data is not available + return None + +# 3. Save Metadata +# Initial filtering - since trait data is not available (trait_row is None), +# is_trait_available should be False +validate_and_save_cohort_info( + is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=False +) + +# 4. Clinical Feature Extraction +# Skip this step since trait_row is None, indicating clinical data is not available +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# The gene identifiers in the data appear to be just numeric values (1,2,3...), +# which are not standard human gene symbols. We need to map these to proper gene symbols. +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# Extract gene identifiers and gene symbols from the annotation data +id_col = 'ID' # Gene identifiers in the data are numeric values (1,2,3...) +gene_col = 'GENE_SYMBOL' # Gene symbols are stored in GENE_SYMBOL column + +# Get mapping between gene identifiers and gene symbols +mapping_data = get_gene_mapping(gene_annotation, id_col, gene_col) + +# Convert probe-level measurements to gene expression data +gene_data = apply_gene_mapping(genetic_data, mapping_data) + +# Preview the gene data after mapping +print("\nGene expression data after mapping:") +print(gene_data.shape) +print("\nFirst few genes and their expression values:") +print(preview_df(gene_data)) +# 1. Normalize gene symbols in gene expression data +gene_data = normalize_gene_symbols_in_index(gene_data) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +print("\nGene data shape (normalized gene-level):", gene_data.shape) + +# Save metadata indicating dataset is not usable due to lack of trait data +note = "Dataset contains normalized gene expression data but lacks trait information." +validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=False, + is_biased=True, # Set to True since no trait data makes it unusable + df=gene_data, # Provide the gene expression data + note=note +) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE53441.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE53441.py new file mode 100644 index 0000000000000000000000000000000000000000..d8b2a9b15211cc54d33c788923673c53763c2b85 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE53441.py @@ -0,0 +1,168 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE53441" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE53441" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE53441.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE53441.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE53441.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# This dataset uses Affymetrix Human Genome U133 Plus 2.0 array for expression profiling +# So it contains gene expression data +is_gene_available = True + +# 2.1 Data Availability +# For trait (SCA vs normal), data is in row 0 +trait_row = 0 + +# No age data available +age_row = None + +# No gender data available +gender_row = None + +# 2.2 Data Type Conversion Functions +def convert_trait(value: str) -> int: + # Extract value after colon and remove whitespace + if ':' in value: + value = value.split(':')[1].strip().lower() + else: + value = value.strip().lower() + + if 'sickle cell' in value or 'sca' in value: + return 1 + elif 'normal' in value: + return 0 + return None + +def convert_age(value: str) -> float: + return None + +def convert_gender(value: str) -> int: + return None + +# 3. Save Metadata +is_trait_available = trait_row is not None +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available) + +# 4. Clinical Feature Extraction +if trait_row is not None: + clinical_features = geo_select_clinical_features( + clinical_df=clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender + ) + + # Preview the processed clinical data + print("Preview of clinical features:") + print(preview_df(clinical_features)) + + # Save clinical features + clinical_features.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# Based on the identifiers (e.g. '1007_s_at'), these are Affymetrix probe IDs +# from a microarray platform rather than standard human gene symbols. +# They need to be mapped to gene symbols for analysis. +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# 1. In the gene expression data, the identifiers (e.g. '1007_s_at') are stored in 'ID' column of gene annotation +# In gene annotation data, gene symbols are stored in 'Gene Symbol' column + +# 2. Get gene mapping dataframe +mapping_df = get_gene_mapping(gene_annotation, 'ID', 'Gene Symbol') + +# 3. Apply mapping to convert probe-level data to gene expression data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +print("\nShape of processed gene data:", gene_data.shape) +print("\nFirst 5 rows of mapped gene data:") +print(preview_df(gene_data)) +# 1. Normalize gene symbols in gene expression data +gene_data = normalize_gene_symbols_in_index(gene_data) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +print("\nGene data shape (normalized gene-level):", gene_data.shape) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data using normalized gene-level data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, gene_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE84632.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84632.py new file mode 100644 index 0000000000000000000000000000000000000000..5d63c96300b26a5f68520162aaa5a7b5594c6618 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84632.py @@ -0,0 +1,147 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE84632" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE84632" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE84632.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE84632.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE84632.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +is_gene_available = True # The title and summary indicate this is gene expression data from PBMCs + +# 2.1 Data Availability +trait_row = 2 # Disease status in row 2 +age_row = None # Age not provided +gender_row = None # Gender not provided + +# 2.2 Data Type Conversion Functions +def convert_trait(value): + """Convert trait information to binary (0: Control, 1: Case)""" + if value is None or ':' not in value: + return None + value = value.split(':')[1].strip().lower() + if 'sickle cell disease' in value: + return 1 + return None + +def convert_age(value): + """Convert age to float""" + return None # Not used since age data not available + +def convert_gender(value): + """Convert gender to binary (0: Female, 1: Male)""" + return None # Not used since gender data not available + +# 3. Save Metadata +is_trait_available = trait_row is not None +_ = validate_and_save_cohort_info( + is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available +) + +# 4. Clinical Feature Extraction +if trait_row is not None: + selected_clinical = geo_select_clinical_features( + clinical_df=clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender + ) + + # Preview the processed clinical data + print("Preview of processed clinical data:") + print(preview_df(selected_clinical)) + + # Save to CSV + selected_clinical.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# The gene identifiers appear to be array probe IDs (16650001, etc) rather than human gene symbols +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview the dataframe by looking at column names and first few values +print("Gene annotation columns and first few rows:") +for col in gene_annotation.columns: + print(f"\n{col}:") + print(list(gene_annotation[col])[:5]) +# Step 1: Extract platform table data from SOFT file - look between !Platform_table_begin and !Platform_table_end +platform_table = filter_content_by_prefix( + soft_file_path, + prefixes_a=['!Platform_table_begin', '!Platform_table_end'], + unselect=True, + source_type='file', + return_df_a=True +)[0] + +# Look at column names to identify probe ID and gene symbol columns +print("Platform table columns:") +print(platform_table.columns) + +# Review some sample rows to confirm data format +print("\nSample rows:") +print(platform_table.head()) + +# Create mapping using probe ID and gene symbol columns +mapping_df = get_gene_mapping(platform_table, 'ID', 'gene_assignment') + +# Apply mapping to convert probe data to gene expression data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +# Normalize gene symbols to standardized format +gene_data = normalize_gene_symbols_in_index(gene_data) + +print("\nShape of gene expression data after mapping:") +print(gene_data.shape) +print("\nFirst few gene symbols:") +print(list(gene_data.index)[:10]) +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE84633.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84633.py new file mode 100644 index 0000000000000000000000000000000000000000..6ff0c944077f6495f1ac69e85fb56d191a2e6156 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84633.py @@ -0,0 +1,157 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE84633" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE84633" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE84633.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE84633.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE84633.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data +is_gene_available = True # Study title indicates gene expression data from PBMCs + +# 2. Variable Availability and Conversion +# Trait: Available from disease field +trait_row = 2 # Key for disease status +def convert_trait(val): + if val is None: + return None + val = val.split(': ')[-1].lower() + if 'sickle cell disease' in val: + return 1 + return None + +# Age: Not available +age_row = None +convert_age = None + +# Gender: Not available +gender_row = None +convert_gender = None + +# 3. Save metadata +is_trait_available = trait_row is not None +validate_and_save_cohort_info(is_final=False, cohort=cohort, info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available) + +# 4. Extract clinical features +if trait_row is not None: + clinical_df = geo_select_clinical_features( + clinical_df=clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender + ) + + print("Preview of clinical data:") + print(preview_df(clinical_df)) + + # Save clinical data + clinical_df.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# The identifiers appear to be Illumina probe IDs starting with '23' +# These are not human gene symbols and need to be mapped to official gene symbols +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# Extract gene mapping info +# 'ID' column matches probe IDs in expression data +# 'gene_assignment' contains gene symbols in format "RefSeq // GeneSymbol // Description" +mapping_df = get_gene_mapping(gene_annotation, prob_col='ID', gene_col='gene_assignment') + +# Extract standard gene symbols +mapping_df['Gene'] = mapping_df['Gene'].apply(lambda x: x.split('//')[1].strip() if isinstance(x, str) and '//' in x else None) + +# Apply mapping to convert probe-level data to gene-level data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +# Preview the mapped gene data +print("\nGene expression data after mapping:") +print("Shape:", gene_data.shape) +print("\nFirst few gene symbols:") +print(list(gene_data.index)[:10]) +print("\nSample of expression values:") +print(gene_data.head()) +# 1. Normalize gene symbols in gene expression data +gene_data = normalize_gene_symbols_in_index(gene_data) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +print("\nGene data shape (normalized gene-level):", gene_data.shape) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data using normalized gene-level data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, gene_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/GSE84634.py b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84634.py new file mode 100644 index 0000000000000000000000000000000000000000..7808a039a80c080325a1a5007282d49c3ccd2e5a --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/GSE84634.py @@ -0,0 +1,164 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" +cohort = "GSE84634" + +# Input paths +in_trait_dir = "../DATA/GEO/Sickle_Cell_Anemia" +in_cohort_dir = "../DATA/GEO/Sickle_Cell_Anemia/GSE84634" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/GSE84634.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/GSE84634.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/GSE84634.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Get file paths +soft_file_path, matrix_file_path = geo_get_relevant_filepaths(in_cohort_dir) + +# Get background info and clinical data +background_info, clinical_data = get_background_and_clinical_data(matrix_file_path) +print("Background Information:") +print(background_info) +print("\nSample Characteristics:") + +# Get dictionary of unique values per row +unique_values_dict = get_unique_values_by_row(clinical_data) +for row, values in unique_values_dict.items(): + print(f"\n{row}:") + print(values) +# 1. Gene Expression Data Availability +# Dataset is about gene expression in PBMCs, so gene data should be available +is_gene_available = True + +# 2. Variable Availability and Data Type Conversion +# 2.1 Data Availability +# trait_row = 2 since disease status is recorded in row 2 +# age and gender not recorded in characteristics +trait_row = 2 +age_row = None +gender_row = None + +# 2.2 Data Type Conversion Functions +def convert_trait(x): + # Binary conversion - SCD patients are cases (1), non-SCD would be controls (0) + # But here all subjects are SCD patients based on background info + if x and 'sickle cell disease' in x.lower(): + return 1 + return None + +def convert_age(x): + # Not available + return None + +def convert_gender(x): + # Not available + return None + +# 3. Save Metadata +is_trait_available = trait_row is not None +validate_and_save_cohort_info(is_final=False, + cohort=cohort, + info_path=json_path, + is_gene_available=is_gene_available, + is_trait_available=is_trait_available) + +# 4. Clinical Feature Extraction +if trait_row is not None: + clinical_df = geo_select_clinical_features(clinical_data, + trait=trait, + trait_row=trait_row, + convert_trait=convert_trait, + age_row=age_row, + convert_age=convert_age, + gender_row=gender_row, + convert_gender=convert_gender) + + print("Preview of extracted clinical features:") + print(preview_df(clinical_df)) + + # Save clinical data + clinical_df.to_csv(out_clinical_data_file) +# Get gene expression data from matrix file +genetic_data = get_genetic_data(matrix_file_path) + +# Examine data structure +print("Data structure and head:") +print(genetic_data.head()) + +print("\nShape:", genetic_data.shape) + +print("\nFirst 20 row IDs (gene/probe identifiers):") +print(list(genetic_data.index)[:20]) + +# Get a few column names to verify sample IDs +print("\nFirst 5 column names:") +print(list(genetic_data.columns)[:5]) +# Looking at the identifiers like '2315554', '2315633', these appear to be probe IDs +# rather than human gene symbols. Gene symbols would typically be like 'BRCA1', 'TP53' etc. +# Therefore these IDs need to be mapped to gene symbols. + +requires_gene_mapping = True +# Extract gene annotation data +gene_annotation = get_gene_annotation(soft_file_path) + +# Preview column names and values from annotation dataframe +print("Gene annotation DataFrame preview:") +print(preview_df(gene_annotation)) +# 1. The 'ID' column in annotation matches probe IDs in expression data +# The 'gene_assignment' column contains gene symbols in format "symbol // description" +prob_col = 'ID' +gene_col = 'gene_assignment' + +# 2. Get mapping between probe IDs and gene symbols +mapping_df = get_gene_mapping(gene_annotation, prob_col, gene_col) + +# 3. Apply mapping to convert probe data to gene expression data +gene_data = apply_gene_mapping(genetic_data, mapping_df) + +# Preview result +print("Gene expression data shape:", gene_data.shape) +print("\nFirst few gene symbols:") +print(list(gene_data.index)[:10]) +print("\nFirst few expression values:") +print(gene_data.head()) +# 1. Normalize gene symbols in gene expression data +gene_data = normalize_gene_symbols_in_index(gene_data) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +gene_data.to_csv(out_gene_data_file) +print("\nGene data shape (normalized gene-level):", gene_data.shape) + +# Load clinical data previously processed +selected_clinical_df = pd.read_csv(out_clinical_data_file, index_col=0) +print("\nClinical data shape:", selected_clinical_df.shape) + +# 2. Link clinical and genetic data using normalized gene-level data +linked_data = geo_link_clinical_genetic_data(selected_clinical_df, gene_data) +print("\nLinked data shape:", linked_data.shape) + +# 3. Handle missing values systematically +if trait in linked_data.columns: + linked_data = handle_missing_values(linked_data, trait) + + # 4. Check for bias in trait and demographic features + trait_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + + # 5. Final validation and information saving + note = "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database." + is_usable = validate_and_save_cohort_info( + is_final=True, + cohort=cohort, + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=trait_biased, + df=linked_data, + note=note + ) + + # 6. Save linked data only if usable and not biased + if is_usable and not trait_biased: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/code/TCGA.py b/p3/preprocess/Sickle_Cell_Anemia/code/TCGA.py new file mode 100644 index 0000000000000000000000000000000000000000..573068cd8ddcbdd7660365b228e1fdb0b534f206 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/code/TCGA.py @@ -0,0 +1,114 @@ +# Path Configuration +from tools.preprocess import * + +# Processing context +trait = "Sickle_Cell_Anemia" + +# Input paths +tcga_root_dir = "../DATA/TCGA" + +# Output paths +out_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/TCGA.csv" +out_gene_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/gene_data/TCGA.csv" +out_clinical_data_file = "./output/preprocess/3/Sickle_Cell_Anemia/clinical_data/TCGA.csv" +json_path = "./output/preprocess/3/Sickle_Cell_Anemia/cohort_info.json" + +# Select TCGA_Acute_Myeloid_Leukemia_(LAML) since it is the most relevant blood disorder dataset +cohort_dir = os.path.join(tcga_root_dir, "TCGA_Acute_Myeloid_Leukemia_(LAML)") + +# Get file paths for clinical and genetic data +clinical_file, genetic_file = tcga_get_relevant_filepaths(cohort_dir) + +# Load the data files +clinical_df = pd.read_csv(clinical_file, index_col=0, sep='\t') +genetic_df = pd.read_csv(genetic_file, index_col=0, sep='\t') + +# Print clinical columns for examination +print("Clinical data columns:") +print(clinical_df.columns.tolist()) +# Define candidate columns +candidate_age_cols = ['age_at_initial_pathologic_diagnosis', 'days_to_birth'] +candidate_gender_cols = ['gender'] + +# Get file paths using proper directory structure +cohort_dir = tcga_root_dir +clinical_file_path, _ = tcga_get_relevant_filepaths(cohort_dir) + +# Read and preview clinical data +clinical_data = pd.read_csv(clinical_file_path, index_col=0) + +# Extract and preview age columns +age_preview = {} +for col in candidate_age_cols: + age_preview[col] = clinical_data[col].head(5).tolist() +print("Age columns preview:") +print(age_preview) + +# Extract and preview gender columns +gender_preview = {} +for col in candidate_gender_cols: + gender_preview[col] = clinical_data[col].head(5).tolist() +print("\nGender columns preview:") +print(gender_preview) +# Select TCGA_Acute_Myeloid_Leukemia_(LAML) since it is the most relevant blood disorder dataset +cohort_dir = os.path.join(tcga_root_dir, "TCGA_Acute_Myeloid_Leukemia_(LAML)") + +# Get file paths for clinical and genetic data +clinical_file, genetic_file = tcga_get_relevant_filepaths(cohort_dir) + +# Load the data files +clinical_df = pd.read_csv(clinical_file, index_col=0, sep='\t') +genetic_df = pd.read_csv(genetic_file, index_col=0, sep='\t') + +# Print clinical columns for examination +print("Clinical data columns:") +print(clinical_df.columns.tolist()) +# Inspect previously given clinical data columns +age_col = 'age_at_initial_pathologic_diagnosis' # Clear age column exists +gender_col = 'gender' # Clear gender column exists + +# Print the chosen column names +print(f"Selected age column: {age_col}") +print(f"Selected gender column: {gender_col}") +# Select appropriate demographic columns +age_col = 'age_at_initial_pathologic_diagnosis' # This is more directly usable than days_to_birth +gender_col = 'gender' + +# 1. Extract and standardize clinical features +selected_clinical_df = tcga_select_clinical_features(clinical_df, trait, age_col, gender_col) + +# 2. Normalize gene symbols in genetic data +normalized_genetic_df = normalize_gene_symbols_in_index(genetic_df) +os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True) +normalized_genetic_df.to_csv(out_gene_data_file) + +# 3. Link clinical and genetic data +linked_data = pd.merge(selected_clinical_df, normalized_genetic_df.T, left_index=True, right_index=True) + +# 4. Handle missing values +linked_data = handle_missing_values(linked_data, trait) + +# 5. Check for bias in trait and demographic features +is_biased, linked_data = judge_and_remove_biased_features(linked_data, trait) + +# 6. Validate and save cohort info +note = f"Sample size after preprocessing: {len(linked_data)}. Number of genes: {len(linked_data.columns) - 3}" +is_usable = validate_and_save_cohort_info( + is_final=True, + cohort="TCGA", + info_path=json_path, + is_gene_available=True, + is_trait_available=True, + is_biased=is_biased, + df=linked_data, + note=note +) + +# 7. Save linked data if usable +if is_usable: + os.makedirs(os.path.dirname(out_data_file), exist_ok=True) + linked_data.to_csv(out_data_file) + print(f"Linked data saved to {out_data_file}") + print("Shape of final linked data:", linked_data.shape) +else: + print("Dataset was found to be unusable and was not saved") \ No newline at end of file diff --git a/p3/preprocess/Sickle_Cell_Anemia/cohort_info.json b/p3/preprocess/Sickle_Cell_Anemia/cohort_info.json new file mode 100644 index 0000000000000000000000000000000000000000..8b29e4efccf59e9aeb11f3ef68c2718e3e8b56f8 --- /dev/null +++ b/p3/preprocess/Sickle_Cell_Anemia/cohort_info.json @@ -0,0 +1 @@ +{"GSE84634": {"is_usable": false, "is_gene_available": true, "is_trait_available": true, "is_available": true, "is_biased": true, "has_age": false, "has_gender": false, "sample_size": 38, "note": "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database."}, "GSE84633": {"is_usable": false, "is_gene_available": true, "is_trait_available": true, "is_available": true, "is_biased": true, "has_age": false, "has_gender": false, "sample_size": 40, "note": "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database."}, "GSE84632": {"is_usable": false, "is_gene_available": true, "is_trait_available": false, "is_available": false, "is_biased": null, "has_age": null, "has_gender": null, "sample_size": null, "note": null}, "GSE53441": {"is_usable": true, "is_gene_available": true, "is_trait_available": true, "is_available": true, "is_biased": false, "has_age": false, "has_gender": false, "sample_size": 34, "note": "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database."}, "GSE46471": {"is_usable": false, "is_gene_available": true, "is_trait_available": false, "is_available": false, "is_biased": null, "has_age": null, "has_gender": null, "sample_size": null, "note": "Dataset contains normalized gene expression data but lacks trait information."}, "GSE41575": {"is_usable": false, "is_gene_available": false, "is_trait_available": false, "is_available": false, "is_biased": null, "has_age": null, "has_gender": null, "sample_size": null, "note": null}, "GSE117613": {"is_usable": true, "is_gene_available": true, "is_trait_available": true, "is_available": true, "is_biased": false, "has_age": true, "has_gender": true, "sample_size": 46, "note": "Data was successfully preprocessed from probe-level to gene-level expression using gene symbol normalization with NCBI Gene database."}, "TCGA": {"is_usable": false, "is_gene_available": true, "is_trait_available": true, "is_available": true, "is_biased": true, "has_age": true, "has_gender": true, "sample_size": 173, "note": "Sample size after preprocessing: 173. 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+NBPF12,3.618789682539682,3.6659126984126984,3.6163293650793653,3.719503968253968,3.678928571428572,3.4925396825396824,3.6654761904761903,3.757142857142857,3.7148809523809523,3.5924007936507936,3.5949801587301584,3.5704563492063492,3.490892857142857,3.45061507936508,3.6858531746031744,3.472261904761905,3.57484126984127,3.7121626984126985,3.520892857142857,3.4964880952380955,3.622579365079365,3.58015873015873,3.571646825396825,3.6463492063492065,3.6034920634920637,3.7969444444444447,3.6085515873015876,3.5896825396825394,3.533095238095238,3.556011904761905,3.4891071428571427,3.695099206349206,3.5199404761904765,3.5326785714285713 +NBPF14,12.023218253968254,12.173865079365079,12.266805555555557,12.630265873015873,12.371,12.281373015873015,12.428571428571429,12.563619047619047,12.153309523809524,12.242424603174602,12.224646825396826,12.459170634920635,11.974916666666667,11.99556746031746,12.568019841269841,12.056142857142857,12.237150793650795,12.509472222222222,12.184559523809524,12.097345238095238,12.398626984126984,12.395563492063491,12.27245634920635,11.759944444444445,12.277873015873016,12.65518253968254,12.326670634920635,12.382706349206348,12.199023809523808,12.00279761904762,12.099440476190477,12.516813492063491,12.233678571428571,11.942511904761904 +NBPF15,8.184884920634921,8.260531746031745,8.07847222222222,8.22693253968254,8.1785,7.778873015873016,8.396904761904763,8.621952380952381,8.378309523809524,8.278257936507936,7.944646825396825,8.172503968253968,7.754083333333334,8.06556746031746,8.443853174603175,8.04697619047619,8.197984126984128,8.40863888888889,8.016226190476191,8.070678571428573,7.973626984126984,8.161396825396825,8.119123015873015,7.910777777777778,8.142873015873016,8.47518253968254,8.239170634920635,8.200206349206349,7.9615238095238094,7.828630952380952,8.099440476190477,8.451813492063492,8.111178571428571,7.868345238095238 +NBPF19,2.2294285714285715,2.2912857142857144,2.352142857142857,2.3974285714285717,2.359571428571429,2.363,2.361428571428571,2.368142857142857,2.2334285714285715,2.3458571428571426,2.2830000000000004,2.3887142857142853,2.2598571428571432,2.298285714285714,2.388,2.3547142857142855,2.323142857142857,2.383142857142857,2.342,2.320857142857143,2.367714285714286,2.3645714285714288,2.344142857142857,2.0944285714285713,2.3127142857142857,2.4015714285714287,2.357285714285714,2.383857142857143,2.318428571428571,2.2192857142857143,2.3369999999999997,2.376714285714286,2.3645714285714288,2.2190000000000003 +NBPF20,14.105678571428571,14.477357142857143,13.689107142857143,14.134392857142856,14.16992857142857,13.704428571428572,13.342142857142857,13.938142857142857,14.420214285714286,14.063178571428573,13.913535714285715,14.255678571428572,13.157892857142857,14.142392857142857,13.914964285714285,14.107928571428571,14.505285714285714,13.492607142857143,13.932892857142857,14.007821428571429,13.862357142857142,14.211714285714285,14.607535714285714,13.92157142857143,14.022714285714287,14.9955,14.947107142857144,13.859571428571428,14.96342857142857,14.857678571428572,13.936107142857143,14.048321428571429,14.002607142857144,14.151678571428572 +NBPF25P,1.008,1.017,1.025,1.056,1.041,1.053,1.05,1.041,1.022,1.0230000000000001,1.0130000000000001,1.043,1.0070000000000001,1.004,1.048,1.019,1.016,1.046,1.012,1.028,1.052,1.046,1.027,0.993,1.017,1.073,1.033,1.041,1.027,1.0050000000000001,1.027,1.041,1.036,1.009 +NBPF26,9.085539682539682,9.213507936507938,9.312698412698413,9.591873015873016,9.372071428571427,9.299944444444444,9.436428571428571,9.54647619047619,9.165095238095237,9.322246031746031,9.254111111111111,9.496492063492063,9.09402380952381,9.077174603174603,9.541055555555555,9.147214285714286,9.26786507936508,9.48286507936508,9.273666666666667,9.15752380952381,9.37826984126984,9.389849206349208,9.321920634920636,8.801373015873017,9.34215873015873,9.58268253968254,9.352563492063492,9.35413492063492,9.242595238095237,9.03011904761905,9.160333333333334,9.539492063492062,9.267071428571429,9.019833333333334 +NBPF3,10.02,10.41,11.11,10.01,10.559999999999999,9.91,11.04,9.78,10.48,10.190000000000001,9.9,10.93,10.82,11.14,11.08,10.719999999999999,10.63,10.5,11.16,10.190000000000001,10.440000000000001,10.510000000000002,10.35,10.91,11.07,10.83,10.31,9.96,10.379999999999999,9.83,10.77,10.36,10.93,9.52 +NBPF4,4.385,4.725,4.37,4.43,4.595000000000001,4.54,4.615,4.555,4.1049999999999995,4.33,4.41,4.635,4.45,4.61,4.87,4.41,4.53,4.745,4.55,4.545,4.79,4.73,4.685,4.54,4.13,4.28,4.390000000000001,4.725,4.58,4.375,4.390000000000001,4.46,4.555,4.375 +NBPF5P,1.535,1.695,1.64,1.46,1.625,1.49,1.645,1.565,1.535,1.59,1.5,1.605,1.58,1.53,1.74,1.51,1.59,1.815,1.64,1.585,1.68,1.62,1.655,1.6,1.55,1.6,1.58,1.515,1.62,1.595,1.54,1.53,1.475,1.615 +NBPF8,10.87345634920635,11.159579365079365,11.207996031746031,11.198837301587302,11.469928571428571,11.098873015873016,11.51547619047619,11.31147619047619,11.26354761904762,10.92206746031746,11.18798015873016,11.236789682539683,11.18122619047619,10.887948412698414,11.483853174603174,11.151261904761904,11.124174603174604,11.221496031746032,10.952892857142857,11.007821428571429,11.301246031746032,11.26615873015873,10.935313492063493,11.139349206349205,11.643825396825397,11.756611111111111,11.118218253968255,11.217349206349207,10.996761904761904,11.017678571428572,11.352773809523809,11.256099206349207,11.25927380952381,11.168345238095238 +NBPF9,7.091789682539682,7.1329126984126985,7.196329365079365,7.455503968253968,7.262428571428572,7.168039682539682,7.320476190476191,7.423142857142857,7.181880952380952,7.222900793650793,7.187980158730159,7.343456349206349,7.0553928571428575,6.994615079365079,7.391353174603175,7.023761904761905,7.16334126984127,7.365662698412699,7.157892857142857,7.084488095238095,7.2595793650793645,7.24365873015873,7.188646825396825,6.921849206349206,7.245492063492064,7.469944444444445,7.239051587301588,7.223182539682539,7.147595238095238,7.018511904761905,7.056107142857143,7.4010992063492065,7.158440476190476,6.989178571428571 +NBR1,25.01,24.14,25.11,25.46,24.58,24.46,25.47,25.299999999999997,24.9,25.419999999999998,24.92,25.09,24.74,25.92,24.89,24.689999999999998,25.25,24.18,24.91,25.519999999999996,25.04,24.85,25.47,24.410000000000004,25.189999999999998,25.29,25.0,25.43,24.560000000000002,24.02,24.85,25.630000000000003,24.61,23.669999999999998 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+NCAM2,5.73,5.79,5.54,5.43,5.36,5.35,5.48,5.9399999999999995,5.359999999999999,5.55,5.47,5.6,5.47,5.8,5.53,5.34,5.539999999999999,5.26,5.77,5.73,5.49,5.57,5.71,5.640000000000001,5.3,5.58,5.62,5.59,5.42,5.63,5.62,5.57,5.6,5.48 +NCAN,3.44,3.56,3.44,3.38,3.55,3.54,3.37,3.48,3.48,3.82,3.01,3.53,3.52,3.34,3.67,3.4,3.62,3.87,3.49,3.56,3.38,3.29,3.74,3.58,3.43,3.49,3.21,3.34,3.42,3.69,3.41,3.15,3.48,3.4 +NCAPD2,6.24,6.44,6.49,6.88,6.35,6.81,6.63,6.57,6.45,6.59,6.74,6.54,6.86,6.75,6.6,6.6,6.99,6.23,6.71,6.69,6.95,6.73,6.44,7.15,7.19,6.91,6.72,7.0,6.8,6.8,6.85,6.67,6.89,6.58 +NCAPD3,7.34,7.51,7.32,7.39,7.17,7.36,7.36,7.36,7.59,7.44,7.43,7.36,7.53,7.47,7.45,7.69,7.54,7.18,7.35,7.42,7.46,7.74,7.32,7.58,7.69,7.59,7.75,7.64,7.51,7.56,7.39,7.35,7.3,7.46 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+NCDN,15.89,16.78,16.11,17.17,16.78,16.25,16.27,16.34,16.04,16.52,16.119999999999997,16.42,16.77,16.71,16.740000000000002,16.98,16.77,16.83,16.6,16.83,17.15,16.57,16.68,17.28,16.66,16.22,16.630000000000003,16.82,16.990000000000002,16.240000000000002,16.4,16.08,16.73,17.04 +NCEH1,5.81,6.44,6.32,6.09,6.66,5.47,6.98,6.75,6.17,5.3,6.35,6.29,6.16,6.47,5.64,5.22,5.51,4.4,6.21,5.77,5.48,6.81,6.28,5.92,5.8,6.04,5.63,6.09,5.52,5.63,5.82,5.84,5.84,5.6 +NCF1,12.629999999999999,13.056666666666667,13.556666666666667,13.773333333333333,14.073333333333334,13.883333333333333,14.083333333333334,13.92,12.33,13.08,13.913333333333332,13.823333333333332,12.863333333333333,13.75,12.783333333333333,12.81,13.426666666666668,12.823333333333334,13.833333333333332,13.36,13.926666666666666,13.96,13.716666666666667,14.016666666666666,12.666666666666666,12.626666666666667,12.03,13.126666666666667,12.969999999999999,13.020000000000001,12.866666666666665,13.59,12.836666666666666,12.846666666666668 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+ATP6V0E2,7.701196429,7.65789761,7.444764088,7.563984437,7.516433464,7.776020629,7.422440278,7.735876634,7.724286084,7.627309532,7.893492108,7.749444664,7.604997152,7.628406862,7.92745219,7.69597268,7.724606139,7.822245661,7.748838846,7.458469284,7.472563119,7.524034761,7.600699275,7.817593439,7.661772557,7.75766321,7.800001865,7.635996729,7.731075814,7.541432016,7.801419249,7.778923981,7.731624479,7.690131683,7.62398325,7.672551539,7.859680622,7.628486875,7.391131569,7.593217203 +ATP6V1A,8.672147634,8.694830452,8.822461007,8.723964347,8.892645217,8.550289095,9.413484779,8.347414233,8.632685445,8.028003791,8.792801388,8.602270097,8.648019074,9.37757123,8.259059673,8.516478444,8.24358366,8.964176596,8.341291734,9.149428738,8.83054402,8.471189475,8.884846972,8.677382973,8.655707794,8.546444735,8.945721478,8.1757214,8.803315877,8.158843456,8.798157206,8.628643939,9.046386752,9.130601232,9.396771124,9.334757548,8.312201649,8.95726551,9.064169289,9.600964275 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+ATP6V1C1,6.626710304,7.495508408,7.19064376,7.205616402,7.750861114,7.384807064,8.195518531,6.993245403,7.465779595,6.88947116,6.963191882,7.450698717,7.366406949,7.447391507,6.637305403,7.202585795,7.107145722,7.289679672,6.815329521,7.295139576,7.031897671,7.104944924,7.173867184,7.13889494,6.969012572,6.847740181,7.334369102,6.897095783,7.296955535,6.965404706,7.198268382,7.473043431,7.60755669,7.852410506,7.848081067,7.544719696,6.656799904,7.363652945,7.029047402,8.30383909 +ATP6V1C2,5.387957158,4.877294652,5.381308024,5.513398881,5.350636214,5.246259489,4.853452597,5.297115767,5.123910911,5.236517209,5.363640971,5.332348273,5.295727238,5.520206058,5.589655075,5.530230559,5.283738477,5.495551206,5.169269518,5.291358452,5.300220201,5.266647155,5.314895708,5.211715602,5.29816563,5.153702192,5.558904243,5.404563059,5.647679774,5.468108007,5.3376879,5.144005068,5.321815775,4.981626222,5.058954857,5.233943351,5.571784823,5.238255693,5.72256712,5.3111297 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+CHMP4A,7.441663816,7.92091813,8.112304317,7.8721189,7.997521149,8.10039881,8.165375452,8.324176229,8.204575032,7.817057446,7.889303608,8.457636844,8.15802098,7.926986176,7.78529729,8.175120735,7.955530267,7.957484178,7.890529353,7.866694066,8.244235785,8.267355042,8.18395581,8.116600494,8.157729713,8.035531393,8.089816137,8.087789409,8.027096808,8.14658878,8.182717929,8.414298856,8.072012488,8.099779869,8.153664122,8.129076398,7.827931385,8.180715474,7.762035003,8.497314434 +CHMP4B,14.875884797,15.183518699,15.86478089,15.299675313999998,15.65199747,15.999659454,16.103837413999997,15.454606814999998,15.513973806000001,15.190729195,15.625030084999999,15.732192981,15.871112055000001,16.939337889,16.043926183,16.384157633,14.947214332,15.65475954,15.808270759,16.067154626,15.462726578000002,16.063322763000002,15.443183014,15.896081165,16.357770862000002,15.34257121,16.110179746,15.686636317,15.952106765,16.174721387,15.985549516,15.677306062,15.332434403999999,16.056505409,15.084122405999999,15.839562724,15.246652749999999,15.871021942999999,15.897552144999999,16.274238451000002 +CHMP4C,6.055680494,5.873448804,5.758990216,6.294496382,5.886849469,5.717086034,5.82904013,6.100652951,5.805599809,5.917109383,6.019771917,5.874684788,6.155263911,6.025854258,6.037726206,5.896379553,6.174985439,5.948746227,5.935323879,5.906126476,5.861847905,5.843297309,5.810164274,5.668221314,5.830720634,6.022807667,5.688593359,5.839784513,6.162647287,5.874977521,5.975786079,5.86060108,5.624137898,5.917911689,5.918811571,6.17698036,6.180601575,5.827056051,5.853309803,6.009248617 +CHMP5,5.690559022,5.715513233,6.756776573,7.064811534,6.382031479,5.595331332,7.002733748,6.327296343,6.202654861,5.72352536,5.374241984,6.711187356,6.250274105,6.28815354,5.703246689,6.129303948,5.355129498,6.29522624,6.088174311,6.725235573,6.95943371,6.053015976,6.243892479,5.725469003,6.146094861,5.784480152,6.046796319,6.17340304,6.515030624,6.06207551,6.290626286,7.008229938,6.331788317,6.92827064,6.625710273,6.580067065,6.098767163,6.163835999,6.283198815,7.061612529 +CHMP6,7.689459071,7.06008773,7.493282414,6.894608487,7.537405963,7.574274726,7.39549681,7.631484508,7.404929095,7.407648313,7.303383325,7.594732587,7.456211834,7.300717217,7.355813233,7.498062288,7.605811273,7.426852785,7.152530496,7.057495976,7.493696669,7.374082974,7.29061575,7.404621059,7.361549082,7.433672072,7.727305052,7.498933287,7.577620638,7.368665784,7.290413933,7.1983748,7.456052505,7.56171959,7.436157607,7.63483042,7.424579689,7.63384258,7.435073867,7.672538488 +CHMP7,7.999016547,8.552531102,8.034890621,7.960911699,8.824917678,9.035801515,8.166637502,8.444868504,9.05411203,9.022144334,8.451015749,8.743660982,8.597984382,8.008191992,8.35354809,8.864910104,9.027938289,8.028067077,8.388725679,7.968098627,8.429434779,8.813773903,8.501839037,8.572194213,7.748877146,8.335984531,8.493188479,8.956341551,7.82283588,8.432563918,8.491805601,8.631324862,8.569085261,8.521946284,8.601598034,7.98486476,8.425730281,8.267688531,7.937540589,8.438564351 +CHN1,4.588015327,5.218920744,7.676367797,4.772374114,5.097327322,5.100792156,4.894467806,4.80056526,4.565883008,5.044363544,4.659692912,5.068858249,4.635717005,4.867610714,4.737836951,5.334297846,4.709794034,5.047374429,4.661508707,4.664853105,4.444335908,4.489888278,4.603431057,5.121034565,4.740310508,4.535653726,4.699167927,4.808597374,4.761812857,4.80306661,4.926883454,4.871686989,4.498717118,5.712344532,4.464708017,4.500847898,4.644342032,5.45861496,4.493556569,4.893924373 +CHN2,7.430211076,7.375416646,7.946576787,7.577972242,7.816172935,7.800711027,8.344393542,7.704171741,7.917054421,7.436127037,8.248704316,7.632456515,8.135784138,7.92855321,8.054787172,7.748593138,7.264426334,8.264258123,7.915503635,7.834414771,7.93685853,7.715130627,8.197034432,8.111522956,7.797368222,7.787649965,8.373755086,7.936100368,8.21586212,7.772601599,8.35508822,7.827028436,8.124388734,8.106801675,8.043701925,7.891667484,7.890610652,8.140631779,8.404191352,8.655643508 +CHODL,4.680884117,4.707817217,4.724898983,4.656520929,4.84813245,4.758522017,4.69554894,4.728509099,4.66866683,4.629465452,4.552133494,4.551582798,4.861063602,4.925433814,4.544841874,4.439893545,4.644823744,4.636859052,4.790217616,4.658509553,4.595638457,4.581228585,4.876911401,4.726653051,4.798508646,4.70030124,4.617666286,4.563606322,4.752505156,4.783986595,4.676774295,4.681016691,4.938895265,4.628282476,4.455435402,4.698853114,4.830734544,4.602144825,4.731527692,4.6662877 +CHORDC1,3.992884651,5.803840042,6.141151012,5.870584649,4.579449436,4.646012949,4.780577412,4.638135342,5.503766609,3.896225511,4.357721971,5.415867911,4.53462857,4.539970855,4.392650555,4.684031456,5.733530138,4.948700932,6.170850495,5.089739521,5.04388868,5.684215868,4.825443552,3.98263018,5.540109993,3.845519077,2.055604592,4.939770714,4.610246804,5.713655027,5.207450885,6.161954232,5.244937428,6.035210784,5.559837965,5.317714742,3.121571547,4.514345997,3.945239973,7.014360699 +CHP2,5.640061079,5.078061051,5.441937988,5.53737756,5.497581555,5.258097126,5.375302817,5.196957757,5.36697342,5.221603173,5.366116486,5.300681023,5.352005643,5.583926203,5.373051937,5.427495797,5.490703233,5.630052092,5.394201063,5.352005643,5.488520908,5.438967284,5.401410733,5.312106806,5.4712794,5.615141444,5.47477569,5.239335989,5.13299622,5.383289439,5.383300865,5.249207867,5.74504118,4.803510892,5.321395969,5.457934085,5.461224711,5.181384414,5.575845328,5.02144368 +CHPF,7.096464517,6.702371481,6.691099128,6.889072508,6.941105347,6.586154807,6.730670231,6.815245024,6.655942674,6.890165455,7.145839995,6.709550642,7.023826417,6.981126486,6.999395842,6.58051863,6.924400405,7.002942561,6.914853194,6.945123534,6.805987122,6.750943322,7.020054679,7.061961688,6.85015503,6.992484561,7.12039148,6.885311485,6.695406624,6.912260124,7.04130285,6.591640971,6.728173598,6.718047767,6.796547062,6.856434117,7.388774205,6.75894755,6.96344409,6.50805071 +CHPF2,8.000559166,8.130655326,8.158129369,7.725200763,8.109116397,8.055687494,8.424939147,8.222939271,8.023179547,7.883079952,8.145293557,8.09913871,8.149130139,8.073055106,7.962888571,8.06522745,7.913321998,7.991585685,7.864978497,8.267845299,7.800232967,8.092740116,8.216296063,8.126561255,7.976226485,8.043289414,8.480209094,8.069257148,8.292332473,7.66825714,8.064429235,8.035049776,7.916205872,8.298756816,8.221008106,8.109760118,8.078552489,8.272222606,8.199677045,8.349213472 +CHPT1,7.194689103,8.030293814,7.754230254,8.893267675,7.71071405,7.809330213,7.908648421,7.468710349,7.938240716,7.605396541,7.421098878,7.828881125,8.072703763,7.956174795,7.341044381,8.041271258,7.446670365,7.570751644,7.944899514,7.797565627,7.764686481,7.807883573,7.610863989,7.765718276,7.296241094,7.629372469,7.573219441,7.701810833,8.175181178,7.413067899,7.548254267,8.16237416,8.195285217,7.377869875,7.6490723,7.958908519,7.136100189,7.834954885,8.074104941,8.421595403 +CHRAC1,7.894597691,7.987861562,7.547375188,7.780469179,7.835252298,8.271666066,7.93249323,7.959198059,7.580481533,7.873028405,7.693774027,8.171224376,8.298287293,8.117492252,7.836267463,7.961909149,7.802492303,7.986404501,8.11144903,8.001930564,7.739587858,8.124646184,7.884434091,8.07974003,7.83128718,7.904868779,7.985938719,8.065539654,8.328527288,7.695828245,7.719403975,8.072036714,8.096962018,8.23607555,7.995003551,8.208594417,7.649668062,8.378365953,8.145018706,8.608574342 +CHRD,6.956674294,6.657317544,6.582300031,6.853420962,6.517356548,6.567221905,6.627523432,6.667161123,6.66644782,6.813805218,6.845168596,6.634393087,6.720549099,6.811632388,6.814957476,6.619600283,6.910079157,6.918518078,6.725454428,6.728856334,6.764323947,6.691413421,6.679473828,6.714798781,6.776625678,6.709147227,6.701366739,6.792856062,6.653125518,6.633262777,6.807626918,6.513373026,6.731281564,6.637454803,6.641723646,6.726244548,6.870748734,6.717838548,6.79274272,6.59274431 +CHRDL1,4.295972299,4.309357021,4.266283368,4.312837947,4.083051908,4.230396142,4.345659712,4.040618296,4.300946655,4.2563908,4.465572002,4.175318908,4.246947385,4.295062767,4.420129073,4.069307865,4.206838133,4.277815339,4.232271351,4.221749971,4.271134207,4.420151531,4.300441359,4.222749334,4.261039521,4.247520053,4.223366917,4.299194963,4.088093637,4.362401844,4.138443549,4.084028813,4.338316081,4.147112178,4.144731673,4.160620417,4.379873847,4.304697072,4.427616895,4.151518147 +CHRDL2,3.418620939,3.474463637,3.142252325,3.895675914,3.514291915,3.191318462,3.529390008,3.598913688,3.375169971,3.355170592,3.581471502,3.611635722,3.182666627,3.51786133,3.450628469,3.491490279,3.287959041,3.861175121,3.433665757,3.321809881,3.447527873,3.476179087,3.551371211,3.490765742,3.848985836,3.485757906,3.619744154,3.504361483,3.116882841,3.434219815,3.487100432,3.755552403,3.372719328,3.525639459,3.409947793,3.519086652,3.259499616,3.685751694,3.616597032,3.629015713 +CHRFAM7A,7.235543937,6.936002816,6.170002981,6.81296515,6.393886691,6.608733607,6.798975278,6.840155605,6.284278388,6.38044589,6.540134046,6.813903146,5.755797527,6.856547663,7.071120043,6.903138627,6.184107243,6.600657687,7.121096946,6.760002674,6.434883994,6.902406532,7.121234213,6.588029054,6.540694556,7.00926948,6.282665491,6.604043625,7.102634432,6.404627893,6.519635394,6.384666873,6.614155683,6.746413166,6.099092746,6.458791461,7.024426128,6.448976817,7.070044572,6.235595608 +CHRM1,5.885833668,5.709055786,5.824572563,5.844694965,5.628148376,5.634901186,4.867082384,5.255461271,5.45404247,5.511281038,6.006898436,5.49714386,5.520958446,5.708919758,6.246958407,5.60441152,5.901884951,6.003721215,5.766712154,5.517810374,5.636183735,5.679372571,5.606141017,5.632899634,5.662961784,5.949174055,5.634182182,6.017518323,5.510853522,5.721764672,5.274825804,5.703420348,5.906956846,5.238059425,5.989117656,5.422610325,5.797065792,5.981616692,5.619308814,5.682865079 +CHRM2,4.061922398,3.422329766,3.907906045,3.710764185,3.684304757,4.440896041,4.338071669,4.207014635,3.585896084,3.808234087,3.63634632,3.767264277,3.742786699,4.301366891,4.739911913,3.859020427,4.158882351,4.378346093,3.805417775,4.23552545,3.384813705,3.758038826,3.795207194,3.568754826,3.669075809,3.910374664,4.282811681,3.504895234,4.459532379,3.803621362,3.869462803,4.122502087,3.339428196,3.449646837,3.733839402,3.509531139,3.54558689,2.964731175,3.597621189,3.84602933 +CHRM3,6.16485236,5.722762953,4.716539219,4.514312578,6.315832834,6.328940555,5.896120383,5.910583422,5.419892139,5.835282739,6.104915101,5.779563077,5.960370015,6.335650799,5.567460626,6.103777772,5.745045131,5.719692163,6.205720395,5.87915522,5.852409024,5.441150721,5.563091386,5.648078324,5.414944757,4.900075747,6.11988046,6.086642009,5.87722176,5.78623541,5.778823813,6.23251398,5.835159528,6.363657535,5.527957386,5.985476561,6.365666817,5.936287066,5.723284578,5.975488483 +CHRM4,6.588662975,6.077255161,6.563180259,6.485040872,6.301785281,5.689951079,6.149553029,6.526927567,6.776141475,5.564156108,6.293619606,5.80185299,5.957187575,6.251764037,4.985959921,6.065167472,6.515140774,5.914605708,6.29821604,6.082090236,6.530372299,5.743002026,5.641641826,6.210873409,6.584014662,6.212958924,5.067647797,6.781028429,5.759852161,5.451507147,6.219018332,5.866358708,6.249554013,5.725819869,6.136230632,5.93112382,6.100475974,5.506612483,6.428069988,5.959157353 +CHRM5,5.466794464,5.627242566,5.833848844,5.462212837,4.989929211,5.566541714,5.62277491,5.660396673,5.687863638,5.518605592,5.510205944,5.88290188,5.485428691,5.638844794,5.894435725,5.523266998,5.370044646,5.694109238,5.458406212,5.224709073,5.613189965,5.421958348,5.457312092,5.505715494,5.718989065,5.473302197,5.644702893,5.445367952,5.199259392,5.590931466,5.46872057,5.677423912,5.604516787,5.623903221,5.424385926,5.228413124,5.431383734,5.407278908,5.508764018,5.105059692 +CHRNA1,5.332558242,4.998488958,5.044270878,5.28619056,4.950579797,5.032637851,5.205129329,5.094595022,5.240706659,5.240840254,5.287105171,5.167907754,5.131611066,5.052152973,5.178184279,5.143634601,5.306127019,5.232505992,5.023162895,5.191420444,5.161001929,5.155432052,5.257344354,5.025742303,5.443339185,5.039605335,5.215385301,5.017346382,4.901786854,5.320668303,5.24310109,5.176653077,5.246307366,5.121910027,5.24815714,5.061165485,5.309549102,5.027694843,5.251514706,5.090374896 +CHRNA10,6.073279022,5.668002656,5.866204741,5.617370869,5.480523343,5.413532455,5.785519584,5.109561962,5.75210345,5.814483758,5.710978342,5.814843298,5.3173236,5.782315442,5.590056352,5.895486157,5.681961294,6.048354393,5.70215902,5.657396206,6.015731364,5.98907248,5.207526222,5.424075457,5.949036568,5.649771829,5.630790196,5.469811146,5.671947029,5.626623754,5.703089596,5.422341201,6.024085397,5.473480575,5.626147891,5.550379981,6.00950285,5.388988516,5.942490395,5.63547096 +CHRNA2,6.580153421,6.33737736,6.017456577,6.547858231,6.309535158,5.977545012,6.128792316,6.08377745,6.215879107,6.044505176,6.179847374,6.113306056,6.203457032,6.26475176,6.304663324,6.172936424,6.33429113,6.467869768,6.300981893,6.383119694,6.264277803,5.766887785,6.303373721,6.132848504,6.403433699,6.434747909,6.353657222,6.169960417,6.226206954,6.036657335,6.237736227,5.852266128,6.234429552,6.772866426,5.940719678,6.496648861,6.754988338,6.387153837,6.533014074,6.31292206 +CHRNA3,5.638221892,5.559671887,5.35165435,5.674593124,5.588369261,5.459329883,5.502035616,5.490727928,5.456596277,5.474501946,5.531962564,5.579257241,5.491265867,5.749410493,5.73655486,5.416239909,5.582440959,5.461130331,5.498533526,5.532588329,5.383337832,5.494691108,5.390056574,5.568487492,5.563986374,5.691927918,5.436000916,5.566182042,5.502771165,5.429611524,5.437713537,5.331377361,5.642360725,5.225897495,5.305226961,5.45017395,5.617736314,5.33739349,5.501502087,5.250550364 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+CLEC4M,3.745480648,3.800117111,3.771322069,4.108709697,3.871358015,3.557942287,3.858492616,3.868869008,3.623707376,3.700800212,3.787406584,3.820737149,3.720081717,3.778623155,3.96377207,3.710313748,3.765813067,3.930043263,3.882353894,3.743511567,3.919556248,3.802772052,4.057214913,3.75722876,3.849156075,3.899234891,3.962975587,3.80762838,3.824973992,3.819420741,3.642015404,3.675467654,3.977633071,3.76479534,3.677016369,3.896591012,3.786123362,3.697348789,3.875796402,3.527444093 +CLEC5A,4.84115213,5.661524152,6.532402834,5.937250492,6.318774321,6.293108931,6.091488995,4.828287327,5.771923857,5.498338082,6.236405331,5.588166946,5.598848371,7.074907949,6.646912427,6.336337667,4.551619137,6.647501082,4.517455699,6.372930647,6.030632696,4.477223756,6.330408299,6.634657685,6.112466544,6.337643412,6.317265222,3.858771351,7.062278608,4.572329116,4.674808726,7.346160506,6.203804507,6.419648506,5.997603758,6.698767644,6.769149463,6.852203434,6.935974971,5.280956341 +CLEC6A,4.847223631,5.977664007,7.093842511,4.644439771,6.12269749,5.205799731,7.679316144,4.889691811,4.999762169,5.338646003,5.283072319,5.633497159,4.308707607,5.907272941,5.210674615,5.92706724,4.954119645,6.611841137,5.543912652,5.879202676,5.182763067,5.545828595,6.054267716,4.836941025,6.102597094,5.860961538,6.994961714,4.788203517,5.678334759,5.066876858,5.071128211,4.732686518,5.756877085,7.116312328,6.442149808,7.05697478,6.15412349,6.243685322,6.601537098,7.604359179 +CLEC7A,8.301358339,8.26250872,8.774914498,7.759383875,8.12699796,7.870172151,9.07895648,7.663328508,8.068980701,7.393758562,8.080890469,8.06372303,8.570368229,8.753243749,7.919765706,7.995270437,6.985603261,8.106470183,8.168007795,9.431197591,8.875084564,7.912805007,8.331738534,8.046281277,8.553600829,8.026016384,8.340790873,7.839826245,8.425919427,7.661465464,8.4510991,8.188889894,8.239054935,8.493377635,9.102455984,9.160438954,7.534732729,8.537599221,8.719802992,9.663544634 +CLEC9A,3.907723815,4.128119933,4.053672939,4.080411088,3.81125657,4.155428713,4.052419588,3.888251025,4.556297144,3.910913236,3.807404809,4.039060704,4.249399447,4.322368914,3.874199231,4.058278748,4.196493781,4.007441621,4.00293771,4.5559405,4.03540255,4.037736024,3.963197321,3.805112094,3.963075043,4.256297971,3.807017595,3.837709403,3.908386155,3.700350316,4.229172608,3.893702591,4.208324189,3.85350366,4.058686342,4.772759983,3.905410721,3.828507974,4.129332443,3.934889933 +CLECL1P,3.713172131,3.933800116,3.893988019,3.67871011,3.849567749,3.370944834,3.725972608,3.964124186,3.532460736,3.784865254,3.69876245,3.725533735,3.636985778,3.302752249,3.675209572,3.946611043,3.467956779,3.604937563,3.703443768,3.606055645,3.629033808,4.030686669,3.69976559,3.576452582,3.627058878,4.609247353,3.000713227,3.599148612,4.146977701,3.722492968,4.175065606,4.138607756,3.729765729,3.588103628,3.42072563,3.88236832,3.911657902,3.489858657,3.390746138,3.656104603 +CLGN,3.060172349,2.868765075,2.951834328,2.948366541,3.108175732,3.134681262,3.018037528,3.078420667,2.986403069,3.149473919,3.132195611,3.005475896,3.004554386,3.083113092,3.069739075,3.04844735,3.054740292,3.192348372,2.948778796,3.135918025,2.857040075,3.059711594,3.218077894,2.999389081,2.978085231,3.059966222,3.152747703,3.114699051,3.104041063,3.028065009,2.98981023,3.099712392,3.116857324,3.134172007,3.042445412,3.124617406,3.147073143,3.18453979,3.071414571,3.047336324 +CLHC1,3.151505773,3.43272354,3.103206027,3.0447838,3.424225428,3.466798584,4.00027079,3.39668457,3.280932205,3.383873161,3.144191523,3.204082106,3.214580854,3.248573303,3.288530949,3.171089975,3.367675355,3.214112816,3.126782323,3.269589153,3.73560874,3.254749577,3.384368731,3.249711279,3.041617657,3.095855068,3.752448952,3.330709485,3.365188326,3.265174907,3.242268548,3.349917421,3.371291182,4.278212287,3.237367909,4.136341534,3.195519754,3.299305014,3.288115703,3.603750891 +CLIC1,9.399702869,8.806961532,9.494458421,8.962126107,9.269856782,9.087186112,9.543574067,9.355972955,9.257197538,8.760522095,9.374495427,9.25922968,9.407698181,9.542974418,9.094659508,9.396615791,8.932188106,9.624471077,9.009942515,9.681470989,9.399291999,8.865926958,9.387954203,9.294608935,9.399081012,9.080323469,9.660216785,8.936407854,9.539643038,9.037270935,9.064044126,9.258463462,9.329077614,9.462987985,9.454326397,9.483387135,9.340870699,9.768630994,9.834737148,9.629551161 +CLIC2,5.054846725,6.367253891,5.350423182,7.878199522,7.235574363,5.024745942,5.379312853,4.40849507,5.802475263,4.04408089,4.674352709,5.230681504,5.710235137,6.915049007,4.474985099,4.339806406,6.002662703,6.246571273,5.246584332,5.158480617,4.623271746,4.395340534,4.886073658,4.370307788,4.604210712,5.489999141,4.301516646,4.412780542,7.612397779,4.393784721,5.807561932,5.405817565,7.284382163,5.065457926,5.096061786,5.336309073,4.985105327,4.365137272,5.105684748,6.873019172 +CLIC3,7.080815568,6.846297246,7.615372862,6.91415864,7.397350731,6.890135747,6.919435403,7.561555932,7.197994014,6.9322086,7.089058619,7.549105596,7.140100961,7.053069682,7.194644329,6.932844233,7.202907558,7.292198866,7.190134361,6.895099738,7.103990951,6.83487603,7.033587025,7.128336705,7.417438753,7.066942625,7.365014161,6.910496183,7.217718817,7.26392833,7.564037928,7.194987369,7.437970709,7.307322896,7.270647879,6.956130599,7.539046451,7.445810183,7.001947153,7.320677598 +CLIC4,10.50371281,9.07293853,9.30250356,9.408828524,9.748666407,9.167780604,9.931547407,8.519842558,8.776475873,9.258159401,9.058631302,9.223411805,9.538871739,9.398592878,8.966428025,9.38321364,9.135847038,9.583308667,9.011555576,9.093832442,9.076010254,9.335055595,9.487786278,9.323768553,8.92890763,9.42675379,8.887748582,8.566495664,9.041149272,8.378440148,9.192271939,9.571609314,9.610356337,9.313079363,8.964881855,10.43988691,8.817521536,9.651309229,9.63249116,9.782895442 +CLIC5,11.308269797,11.771473408,10.893794665,12.081270659000001,11.765892491999999,11.862223955000001,12.078338978,11.298735257,11.720792804999999,11.308209221999999,11.6747865,11.43913459,11.41994531,10.879101989999999,11.573626223000002,11.06637492,11.826763285,11.456303493,10.775093836,10.822479352,10.673272092,12.112154191,11.722841981,11.807275455,11.495533993999999,11.014349567,13.060086777,11.991138056,11.408541648,12.052275387,11.977822021,11.200280532,11.519585164999999,12.411044645,10.814701292999999,11.325246238,12.071934806,11.005367504,10.657025484,11.262493535 +CLIC6,4.838551279,5.0088272,5.120701843,5.272195443,5.009316323,5.137429847,4.93818562,5.019343343,5.004156076,4.84882286,5.103448031,5.28103634,4.828976697,4.961810258,5.195415371,4.86780083,5.188616562,4.963412135,5.127341686,4.931814794,5.021030817,4.923230686,4.771174595,5.009353007,4.969893014,5.084775763,5.07083576,5.22499508,5.11392749,4.914328649,5.268820495,4.856722196,4.955671765,5.081669832,4.777203035,4.950841676,5.150856271,4.905328787,4.96559587,4.661446955 +CLINT1,8.937077424,9.310687125,9.346657361,8.708967508,9.448804,9.514906819,9.314648389,9.34893846,9.220669557,9.18602383,9.166070345,9.313238032,9.461190614,9.342536666,9.112807906,9.375097517,9.116793698,9.315972898,9.162366625,9.145086685,8.902676977,9.160845892,9.232700515,9.24530788,9.073563189,9.119602148,9.182663502,8.961237452,9.226102497,9.090781809,9.137703773,9.511301211,9.490955278,9.333583965,9.478286593,9.39495289,8.877548094,9.558873166,9.338174239,9.574239614 +CLIP1,7.571799779,7.509036313,7.883673506,7.435691032,7.503876115,7.374848434,7.941765515,7.473812847,7.391817984,7.083820088,7.321575641,7.626663822,7.490395951,7.506592607,7.37158637,7.370404299,7.13185312,7.575664244,7.351718472,7.816465906,7.549806424,7.601703922,7.538258492,7.53528058,7.628914305,7.509070412,7.649350507,7.063656671,7.878615603,7.492839657,7.549613201,7.575902932,7.405866452,7.911077113,7.435531907,8.123997793,7.34656964,7.702225487,7.484841833,8.182623232 +CLIP2,7.901341806,7.178544113,6.926766453,7.044039885,7.400608522,7.4935142,7.374054412,7.399163794,7.056098552,7.322179025,7.261355953,7.322390919,7.44073345,7.462577746,7.323864542,7.078645949,7.339034192,7.486194242,7.248796446,7.430716665,7.376934237,7.280503422,7.368891915,7.361851271,7.256578717,7.272412942,7.312133346,7.224910268,7.476562718,7.134913311,7.433008968,7.316939476,7.353548898,7.335191214,7.32220792,7.850679992,7.351959696,7.500314055,7.490209873,7.362883503 +CLIP3,7.226212768,6.911788227,6.843228951,7.085628719,6.969447123,6.951965382,6.836133421,6.815083348,6.85382083,6.91405057,7.260682648,6.925444552,6.855877505,7.003217734,7.18054429,6.863075869,6.987566434,7.009727111,6.948129682,6.916282063,6.923151359,7.029100994,6.957621239,7.124355917,7.023157202,7.126597693,6.814260678,6.968377652,6.787698715,7.043312621,7.033965032,6.658035612,7.217019429,6.69353383,6.708352176,7.023733071,7.251921211,6.982959481,6.946968234,6.790231572 +CLIP4,7.585626133,7.78474493,7.917918399,7.186573193,7.49369839,8.071692988,8.556792296,8.039329117,7.802182501,7.469683681,7.932562045,7.663105914,7.857408723,7.989690745,7.360361852,7.892338221,7.674705595,7.836720632,7.102494531,7.428590153,7.501330045,7.810694731,7.935127672,8.006921761,7.70952638,7.788810797,7.826806003,7.640232691,8.070910254,7.878433824,7.718321265,7.749750204,7.721832696,7.954761247,7.894903849,7.529399751,7.420512774,7.942857169,8.027708514,8.323796695 +CLK1,8.950417726,9.377429549,9.2134953,8.399555511,8.824289291,9.228763033,8.73222244,9.402766715,8.986951229,8.670860696,8.647946979,8.864663962,8.930533322,8.805059218,8.540260996,9.188388362,8.564871126,8.521200564,9.87323099,9.377587074,8.834564717,9.240734874,8.727351306,8.907256089,9.176283231,8.615133472,8.290039822,8.843858647,8.786713705,9.14625669,8.666110734,9.792905752,9.180136516,9.004751467,9.074995154,8.69999056,8.081695858,8.859744359,8.20492085,9.114038941 +CLK2,8.409057322,8.483390756,8.285074468,8.282238002,8.627386458,8.593686533,8.723060925,8.404194808,8.547616463,8.679354577,8.57702792,8.721969111,8.85797318,8.711141012,8.37360149,8.732301953,8.821380511,8.580821131,8.568991265,8.579695549,8.598155094,8.581980481,8.847100059,8.646937816,8.221344017,8.56404996,8.904876181,8.555630607,8.33480268,8.454924788,8.491112248,8.703250683,8.546153207,8.578952665,8.877198121,8.53335534,8.703115613,8.597288396,8.758472372,8.86597337 +CLK3,9.140747398,9.352352603,9.733445554,9.761360197,9.703878307,9.231341251,9.409523132,9.208288618,9.514966473,9.142124569,9.34024548,9.365130348,9.448467112,9.565311028,9.301133845,9.205713909,9.379428968,9.494404722,9.391416337,9.629235679,9.28547003,9.476513484,9.323444003,9.265411246,9.303421145,9.435114549,9.477243983,9.316342595,9.837619503,9.080104005,9.385368763,9.469759362,9.474477667,9.219808947,9.178613593,9.319623853,9.204396615,9.492249151,9.380666362,9.701292542 +CLK4,6.498685278,7.54337141,7.326993305,6.807976012,7.495519624,7.913263751,7.278551363,7.390385856,7.477716596,7.436368816,6.832061739,7.549076248,7.516039827,6.996604507,6.812070217,7.831182938,7.327915423,6.960715668,7.459286527,7.054673363,7.355025698,7.587460954,7.427356648,7.199359853,7.100545669,7.166888999,7.367492736,7.367357492,7.201536052,7.446868669,7.241900239,7.903464708,7.362660836,7.414041261,7.607501656,7.28104723,7.232924955,7.377451612,7.049010476,7.834829512 +CLMN,6.921328899,6.850076302,6.759347312,6.265538072,6.806606058,6.827694363,8.232027595,6.57244785,6.610445813,6.601770244,7.054398769,7.1195528,7.143936794,7.284932746,6.832612229,6.580343131,6.595507408,6.718176864,6.952119466,7.399101171,6.823987996,6.830938717,7.03325913,7.03880328,7.009059941,6.924737524,7.049398767,7.015363845,6.874727237,6.515702447,7.074655451,6.746914042,6.90721185,7.045497328,7.452242877,7.681596155,6.731072146,6.746072152,7.485588359,7.110139908 +CLMP,5.672447443,5.340013292,5.468022725,5.270831416,5.301174161,5.248170907,5.297437421,5.218965885,5.33734121,5.068442073,5.360168724,5.339053012,5.517216174,5.434611261,5.433838862,5.384196587,5.523917255,5.474473298,5.170753591,5.327581847,5.306914962,5.22114739,5.322550818,5.536807963,5.499691073,5.481404011,5.359302384,5.261583507,5.314816393,5.355429953,5.484921557,5.448587503,5.594529112,5.252867927,5.251834583,5.324669695,5.526265764,5.331172458,5.403297452,5.087777422 +CLN5,5.481783675,6.280009584,6.310160764,5.912687173,6.202684072,6.181949399,6.30622629,5.983560149,6.189293749,5.994471754,5.740829386,6.382030473,6.289281826,5.955153253,5.555581276,5.789590623,5.831518992,5.748829481,5.820961489,5.942431789,6.06825624,6.199825022,6.071849726,6.071862841,5.699071511,6.045042849,6.115325654,6.283589955,5.941395711,5.611293415,5.975219066,6.335616805,6.209661205,6.467592149,6.355013757,6.227772896,5.780593794,5.794010348,5.889093913,6.886511034 +CLN6,7.19524511,7.461784209,7.474101953,7.100873026,7.622362568,7.331533338,7.205580247,7.383068324,7.257652455,7.436816154,7.328066974,7.512129631,7.593160689,7.736471183,7.057664989,7.134577342,7.339425392,7.584091862,7.199683591,7.570891538,7.485601073,7.367424917,7.515148309,7.632608169,7.367757483,7.552651555,7.738875893,7.302420996,7.381226418,7.176826053,7.694043397,7.27870646,7.50630972,7.56244947,7.47507407,7.58496165,7.489093019,7.351500107,7.443448761,7.948956525 +CLN8,6.324583954,6.473379822,6.47949946,6.526337398,6.619418609,6.637734275,6.657931244,6.648903156,6.415621682,6.352998105,6.326270639,6.329416955,6.523656002,6.78531919,6.189335625,6.557411321,6.338120681,6.531267707,6.395900445,6.332379465,6.505124094,6.253754008,6.652687384,6.216203648,6.416692078,6.609039011,6.491695488,6.528532251,6.71229439,6.210538117,6.652795505,6.52931072,6.280849084,6.558103294,6.878151723,6.491500871,6.272123734,6.468871184,6.507898522,6.907525625 +CLNK,3.866321095,3.818735352,3.774772943,3.864295029,4.109288174,4.168419275,3.990404216,3.829262317,4.239074295,3.884502086,3.896133204,3.79217138,4.14241274,4.039619388,3.991894286,3.93329918,3.891341398,3.867607486,3.879463722,3.8542719,3.732407803,3.858173953,3.850294808,3.844216611,3.821372453,3.834386441,3.940288571,3.897644713,3.92907553,4.021234718,4.073322829,4.036982286,3.842415664,4.012133502,4.053137212,4.164367144,3.882379541,4.036896527,3.875710271,3.948049998 +CLNS1A,6.889972895,7.584559934,7.389515682,7.334084486,7.291536446,7.102849705,7.477364933,7.365189005,7.596633952,7.352831264,7.342743312,7.766111551,7.437664638,7.369833667,7.258435352,7.446911927,7.028451057,7.648513349,7.178603921,6.795251226,7.519744841,7.388443837,7.557784828,7.403165942,7.609191351,7.41077394,6.937165597,7.233089372,7.127838403,7.332886542,7.577761075,7.460394055,7.746334961,7.458208332,7.476440204,7.400213115,7.370138407,6.883247594,7.3777103,7.764351953 +CLOCK,5.847897933,6.986413762,6.728985043,6.151985976,6.707437262,6.896434666,6.830162849,6.633495096,6.73594736,6.465514449,6.336121559,6.780258377,6.722943168,6.479356479,6.192107803,6.731203544,6.606896685,6.880315132,6.710812216,6.479073266,6.268020658,6.827873545,6.659833895,6.49914598,6.277378484,6.331590152,6.604312367,6.382037449,6.583791233,6.752149497,6.548908845,6.991594198,6.430679263,7.10214163,6.957632252,6.609693412,6.303658281,6.44817946,6.251609791,7.220800789 +CLP1,6.547477557,6.789886843,7.389601009,6.572960949,6.645380642,6.633127978,6.75008718,6.946903658,6.589781492,6.335968631,6.643274044,6.631924208,6.704580356,6.617059792,6.599261185,6.801000224,6.739865879,6.658794085,6.57363807,6.697003051,6.787672765,6.601743962,6.721916801,6.662867559,6.975708166,6.535525836,6.740500008,6.770938205,6.698754967,6.643198808,6.813371116,6.850086116,6.594962005,6.743681402,6.788919527,6.697432969,6.516899637,6.892927448,6.652582041,7.168229332 +CLPB,6.793243618,6.984136397,7.221887536,6.900495315,7.333360598,6.890117289,7.362486806,7.001505681,7.120090956,6.847952023,7.092512985,7.063580307,7.354298083,7.19660773,7.1034716,7.017568639,6.99675211,7.223387391,6.966767114,7.109083959,7.059044456,6.909990362,6.991684053,7.292017832,7.066737259,7.044868412,7.337799683,6.979697312,7.520007821,6.842279186,7.096117474,7.054665849,7.223593016,7.406079353,7.392266176,7.183375142,6.958771922,7.443103988,7.192066687,7.613859983 +CLPP,7.467692936,7.803714539,7.934045848,7.588699359,7.953781174,8.009513387,7.723503141,8.329295139,7.912877595,7.952684767,7.994663043,8.042915805,8.087000051,7.901121072,7.717293786,8.106029768,7.92818387,7.96308435,7.815319084,7.714058843,7.732914872,7.850078442,7.793141267,7.825588401,7.810868323,7.751705768,8.051893316,8.056181244,7.863430725,7.735183674,7.771126284,8.029433256,7.658565452,8.147356713,7.826435131,7.872408236,7.969575948,8.070977311,7.73730507,7.879393539 +CLPS,5.698568712,5.318347165,5.698589127,5.533165347,5.390494226,5.703805193,5.603250481,5.331841564,5.592144651,5.444900542,5.507993494,5.748289756,5.204012241,5.481923376,5.793907359,5.624186194,5.678071924,5.686564617,5.753832463,5.97424439,5.718299933,5.367547623,5.900882629,5.496091475,5.836574976,5.387105315,6.035826623,5.548099013,5.212851992,5.716380911,5.663250541,5.208973118,5.621848662,5.433539523,5.610875531,5.663250541,5.965210696,5.824193201,5.430701598,5.59284444 +CLPSL2,6.042201625,5.524192024,5.987037202,6.043144121,5.5327994,5.48809328,5.789998695,5.710885782,5.620065474,5.876719712,6.080821263,6.028586527,5.631136967,5.965246233,6.009509494,5.985277119,5.842528671,5.971196451,5.733335363,5.931202812,6.017798919,5.896103341,5.933587441,5.890618694,5.949643945,5.881591169,5.804249694,6.163919914,5.387246174,6.0805828,6.03256091,5.863910846,5.743248607,5.876549381,5.928477521,6.144275111,5.993907205,6.011712437,5.904785988,5.783611102 +CLPTM1,8.971575946,8.977053094,9.533533878,9.215204175,9.204564357,8.984744686,9.335976583,9.337666898,9.200816836,8.946627409,9.140555112,9.37991169,9.432652163,9.167573958,9.050509763,9.240047886,9.067740501,9.185551581,9.100642695,9.243336795,9.238488602,9.024381936,9.183546787,9.275832788,9.346367439,9.149308065,9.369311182,9.244411259,9.379020671,8.889078053,9.259362037,9.268403261,9.205206415,9.252731806,9.235107971,9.290927701,9.167390513,9.274679705,9.335406157,9.581738772 +CLPTM1L,7.995205155,8.108871389,8.323190554,7.905880607,8.328794998,8.217303622,8.2735512,8.43833856,8.23785723,8.262163067,8.277972616,8.285704119,8.349444204,8.269452428,7.995695095,8.218821243,8.373845639,8.355610287,7.938312289,8.132364641,8.132794833,8.044187271,8.451292113,8.3181836,8.206309832,8.176256154,8.370702849,8.099944909,8.433964943,7.985776784,8.328388705,8.258422789,8.159108231,8.648965246,8.330599413,8.194443708,8.46458026,8.374789671,8.426026716,8.426352187 +CLPX,7.538647534,8.340693083,8.527038142,8.627009259,8.809526595,8.062282531,8.285503823,8.216729899,8.442315373,8.075779632,8.040917332,8.363797018,8.302866174,8.431370087,7.866593324,8.04764712,8.453610909,8.114419619,8.083009775,7.923796516,8.176351175,8.028721156,8.190160999,8.074516233,8.040629628,8.171172491,8.148831599,8.161202899,8.655479511,8.254031434,8.309458363,8.42589119,8.62688417,8.233792037,8.439813594,8.25067905,7.918017405,8.171948043,7.828428571,9.002196965 +CLRN1,4.192386624,3.916502293,3.814834005,4.325758434,4.140856606,3.959103901,4.049201819,4.078015697,4.202718575,4.149230676,4.132022552,4.005526915,4.20656357,4.125205351,4.188753928,4.102418445,4.282354802,4.235377448,4.094468975,4.033621331,4.144784163,4.075904487,3.948736566,4.130677983,4.088972755,4.257621809,4.217744723,4.080881752,4.179306562,4.262882141,4.179023495,4.094150525,4.049661803,4.027311292,4.100755425,4.064086434,4.464308014,4.224408596,4.09592364,3.944368189 +CLRN3,4.24662407,3.831918759,3.899016527,3.781071065,4.043106178,3.52003172,3.903889431,3.767426934,3.808359327,3.877438037,3.81287206,3.708125812,4.199653513,3.976834684,3.969991432,3.723231814,3.75156881,3.686483763,3.989207623,3.899196613,3.72114494,3.982925814,3.95601891,4.054726994,4.02454677,3.924217915,3.971252031,3.696113045,4.073890219,3.830880618,3.864673148,3.855954887,4.244611349,3.62841146,3.894302522,3.739587822,3.60177998,4.002692855,3.857842068,3.88359279 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+KLF10,8.628622812,9.141781322,9.156807713,8.305869455,8.587466927,9.147627603,8.827889188,8.812205694,8.375928193,8.102302922,8.405594445,8.604097422,9.265683823,9.577092495,9.142989231,8.955821274,8.1870595,9.725153182,9.780514079,9.840899879,7.993774691,8.738697168,8.972693351,9.153744455,9.734111037,8.935083888,8.837069298,9.195567106,9.508318973,8.965146334,8.905050432,9.325857031,8.801218551,9.475357545,9.083666391,9.423233844,8.607595527,10.26513694,9.243350327,9.421036054 +KLF11,8.300140982,8.263803155,8.637405016,7.571071829,8.014361261,8.408696519,8.436321969,8.201465579,7.810908355,8.142276365,7.694338805,8.023016395,8.648430009,8.395175734,7.692770348,8.038632273,7.456127978,8.328212926,8.368534863,8.337829743,7.677085779,7.804096444,8.163341772,8.470541806,8.129362354,7.801818174,8.12923642,8.40665867,8.42436964,8.080305143,8.228014861,8.548976101,8.213601085,8.296969722,8.32623232,8.256121151,7.67552877,8.739366164,8.667165209,8.750524755 +KLF12,7.895771132,9.047975542,9.319711717,8.59016386,8.968674828,8.93907297,8.27459776,9.28991111,9.106734997,9.192816547,9.238189696,8.982774292,8.782879909,7.819697162,8.817742761,8.865115088,8.884382016,8.416796577,8.800767288,8.297570766,8.408308841,8.981792239,8.87653729,9.074619552,8.637173763,8.794021525,8.984060312,9.017800819,8.78608327,9.204881759,8.862239078,9.156574145,8.560620457,8.922436538,8.406777307,8.163438806,8.8963537,8.93886253,7.44103497,8.919562977 +KLF13,9.147365333,9.354094112,9.88264201,9.113362918,9.343793448,9.270314614,9.51031897,9.505662661,9.516179106,9.456737342,9.378363705,9.59178167,9.61523357,9.450195795,9.282296093,9.370073203,9.312550747,9.315083325,9.555780449,9.379158685,9.510671033,9.498428346,9.42066798,9.587613706,9.79771547,9.371731304,9.758295836,9.553588577,9.490841969,9.262671453,9.451535904,9.38047608,9.396932159,9.440394832,9.564207233,9.052546975,9.492693136,9.489081657,9.407896485,9.912358069 +KLF14,6.884233028,6.750713946,6.732743093,6.913358205,6.831548361,6.625640936,6.555880515,6.679886291,6.905910514,6.936183255,6.824513793,6.77710792,6.786414665,6.848497883,6.842794489,6.87701485,7.12150338,6.929619188,6.931937268,6.873285267,6.843219088,6.826269566,6.741315397,6.708586869,6.890533155,6.792565609,6.987938395,6.845835534,6.738033363,6.663682686,6.845537167,6.853156993,6.795159104,6.743300682,6.701116226,6.776614468,7.139439806,6.673425505,6.93597698,6.741474645 +KLF15,4.428026677,4.434345451,4.097555833,3.86026898,3.895457484,4.382125957,4.326240141,4.068901167,4.185322269,4.231182025,4.375674049,4.700532757,4.194754345,4.731133236,4.047302636,4.361899737,4.613872362,4.674643194,4.170534086,4.856208089,4.315917088,4.375715013,4.240399037,4.410207121,4.327755828,4.32321901,4.516755779,4.400478052,3.933820736,4.867893212,4.013230415,4.249841353,4.203111103,4.614476588,3.900414188,4.382853077,4.591751533,4.329363684,4.261718859,4.285389406 +KLF16,8.307725561,8.099448711,8.216504594,7.977949722,8.1145378,8.075885271,7.933730829,8.153964128,7.982954457,7.723219945,7.975653285,8.036646152,8.082038224,8.175892606,8.099174137,8.193590147,7.921736938,8.368031994,8.23034562,8.278483432,8.000077889,8.162101503,8.092197462,8.091511027,8.450953338,7.910679095,8.335095596,7.944726269,8.243674939,7.925169113,8.143093495,8.296405625,8.187636884,8.015853413,7.916307862,8.270658073,8.26589047,8.035809949,8.245605072,8.50342266 +KLF17,5.274810365,5.00177672,4.944693687,5.34201126,5.087086872,5.150457842,5.282618839,5.107917092,5.174980795,5.494602335,5.288438039,4.915357604,5.167332378,5.158929408,5.476973247,5.294680245,5.306730219,5.307736288,5.206260422,5.126243569,5.131171025,5.22642755,5.426486832,5.29238229,5.35549031,5.153521782,5.52613348,4.995363024,5.362715721,5.488051449,5.353226652,5.153979087,5.136235672,5.392497676,4.989635286,5.204682722,5.418872712,5.559310921,5.199892699,5.119244758 +KLF2,10.17919688,10.21299983,10.34409339,10.30650719,10.50060568,10.27765991,10.33852689,10.44038894,10.58227068,10.64973865,10.49158105,10.56836921,10.41702934,10.32066483,10.23878307,10.46592588,10.37473378,10.30565005,10.27285203,10.35295053,10.39614264,10.3252067,10.34523625,10.5783495,10.3634924,10.47815248,10.69656622,10.51177809,10.52312784,10.22843825,10.4152855,10.24328553,10.24098997,10.32380768,10.31088158,10.33617221,10.42071407,10.35784709,10.25497746,10.47780903 +KLF3,9.50868478,9.578337754,9.874319467,9.730692778,9.751286869,10.00978234,9.362202926,9.986159389,9.595381888,9.6607684,9.521267043,9.342607599,9.889083813,9.712269913,9.241276418,9.623748974,9.837593157,9.599952322,9.09666182,9.479188656,9.11824382,9.399048654,9.650574488,9.61420643,9.549536423,9.565201828,9.272791783,9.247334143,10.39290627,9.700273882,9.566417715,9.633541209,9.652593729,9.671548544,9.378769391,9.554834218,9.13763288,9.697169027,9.63070655,9.978125313 +KLF4,8.072776413,8.203596914,8.406931784,7.968331716,7.961151211,7.522562056,9.345995568,7.727970323,7.827351564,7.206379772,8.061787403,8.756233873,8.625773487,8.952628315,8.361284289,8.230027283,7.361961011,8.790324901,8.644892399,9.165326213,9.293745938,8.324694271,8.34084495,8.573567508,8.917227772,8.540371314,8.603609954,7.965210706,8.773486727,7.74906442,8.470912481,8.408088521,8.282888019,8.388293027,8.877080239,8.438894851,8.073300218,8.1032008,9.290584043,9.599148451 +KLF5,7.165692868,6.981396138,7.060697258,7.26808778,7.149695553,7.295183421,7.126097749,7.180107588,7.035668063,7.083196317,7.41633763,7.067823976,6.927870151,7.159443129,7.354515618,7.165854152,7.091734267,7.1337688,7.266353982,7.305999501,7.149766115,7.519176072,7.063136672,7.200378918,7.41228538,7.192879231,7.002806534,7.103255963,7.604827732,7.253027926,6.961013926,7.468916077,7.321039195,6.78811793,7.01483224,6.990095371,7.160531793,7.30727969,7.248872432,7.356908127 +KLF6,9.367411904,9.491803597,9.347621235,9.620385807,9.271496681,9.05735173,10.28210656,8.940417253,9.919931593,9.519556249,9.689662674,9.991551341,9.47524153,10.69988208,9.672672032,9.888350331,9.706119978,10.00241811,10.53707096,10.06554254,10.01069438,10.05369481,10.13952422,9.486594022,10.29374477,10.47482273,10.05552339,9.772530151,9.895893262,9.711796224,10.06409491,9.53747071,9.422060058,10.04507567,10.36365974,10.15447674,10.27670651,10.23018225,10.01147886,10.35471904 +KLF7,8.107806618,8.148384305,8.059971904,7.652582361,8.280516732,8.555678985,8.850549044,8.097490257,8.295196795,8.05118521,7.635862741,8.236784847,8.000469031,8.442720759,7.744196391,8.489179958,7.992310805,7.66588691,8.126636941,8.512895731,8.192768373,8.235468622,7.913183129,8.282532573,7.55525283,8.103869799,8.022880436,7.910953847,8.465333749,7.898372629,8.168957738,8.162744205,7.783019111,8.488148322,8.411664955,8.216780593,7.673096505,8.483310304,8.678665099,8.703570574 +KLF8,5.753711193,6.612406239,6.129143442,5.802098478,6.603169736,6.499331328,5.750371924,5.852230318,6.194216368,6.423716161,5.756857811,6.471996418,6.307655173,5.672980095,5.850592792,6.362763807,6.164569657,5.776165633,6.180227829,5.626283849,6.277248564,6.12925047,6.358140204,6.628920634,5.720553969,6.411664826,5.978758628,6.087691561,5.659569507,6.363288243,6.234073535,6.601071991,5.862933101,5.807471276,5.921006406,6.038490864,6.085925602,6.320284458,6.04716054,6.481977275 +KLF9,7.665833419,7.729727204,7.742223879,7.118053883,7.324689765,7.767113521,7.752822718,7.524978787,7.534685748,6.974264348,7.264083486,7.541457804,7.645620956,7.528546303,7.724490009,7.340567282,7.509308684,7.451678792,7.770349174,7.472710539,7.523215771,7.417102931,7.516474826,7.374738686,7.727736033,7.714337109,7.048508075,7.480198173,7.409708633,7.255786939,7.414956199,7.694975042,7.620482418,7.528152217,7.358415229,7.457704159,7.297725986,7.78877788,7.900122977,7.390396019 +KLHDC1,7.01269672,7.212433835,5.812554941,5.968465929,6.731850651,7.275567524,6.144995289,6.590132924,6.736857509,6.32108413,6.135379112,6.807318832,6.1818376,5.994649864,6.075801797,6.287551073,6.299907054,6.38999827,6.358624823,6.265847524,6.445772092,6.492928961,6.351297189,5.936501544,5.774960527,6.361482815,5.866760092,6.342390139,6.348879715,6.377846431,6.377534846,7.005207921,7.287805317,6.583213575,6.354660165,7.71080963,5.618071805,6.424315663,5.854420077,6.719289019 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+MOV10,7.373442741,7.505704973,8.320121811,8.113318585,7.912556939,7.892583481,7.918465602,8.018272476,7.754110506,7.539888223,7.763257456,7.850219934,7.944625636,7.311347399,7.424034917,7.953772586,7.80966886,7.452297421,7.554955919,7.621775775,7.841205899,7.896438008,7.77322606,7.676137897,7.461130208,7.62964191,8.121341801,7.838402607,8.471112936,7.666930531,7.735913272,7.768078635,7.363437887,8.445206648,7.830016896,6.936044555,7.799494842,7.741556106,8.095755098,8.082393635 +MOV10L1,4.319665088,4.424934555,4.486455519,4.532110736,4.326644604,4.23456913,4.330469803,4.405102371,4.249552139,4.328798485,4.292264896,4.307059587,4.241866432,4.352691264,4.269843347,4.288686864,4.244514647,4.404360871,4.268631053,4.297478936,4.370710893,4.31203823,4.311485048,4.399099751,4.396522156,4.403195656,4.427441531,4.423333856,4.328857334,4.137491473,4.423239697,4.199895176,4.369898773,4.215160661,4.340721335,4.469612875,4.506887965,4.468847835,4.310414206,4.221997096 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+ATP1A1,4.7278554785,4.639136974,4.7277131525,4.809134701,4.7858041485,4.8780096455,4.4871708845,4.9124690145,4.8721797445,5.02868385,4.5313303325,4.6050224725,4.727444922,4.8447272055,4.7153424415,4.744621575,4.7984388405,4.859989001,4.82859713,4.790310095,4.5447998905,4.607509985,4.8190552905,4.9853309405,4.5995101215,4.8849966305,4.721294009,4.8607484815,4.8906351995,4.939071659,4.6717206295,4.420346313,4.832127565,4.6066814605,4.8616598585,4.9173827305,4.673768926,4.7477791735 +ATP1A2,2.4866638315,2.657984211,2.461850736,2.49684863,2.490866997,2.5331710285,2.6525259705,2.53095462,2.47860999,2.4280918945,2.577851691,2.5843246725,2.4919191235,2.4819746585,2.548424045,2.5935016295,2.4647342975,2.4838022035,2.47658757,2.5266090285,2.527385989,2.6778573435,2.518585061,2.5291249005,2.5143441515,2.542051119,2.497449885,2.4334385125,2.4419619545,2.444820059,2.6075932885,2.6157652485,2.5147002585,2.4896664055,2.6101970315,2.495891339,2.5402844585,2.491072334 +ATP1A3,1.937879559,1.880104804,1.948794485,2.191165322,1.9176676145,1.865555535,1.9259355965,2.198077117,1.775785474,1.939360658,2.0035951455,2.185169548,2.1553988645,1.957663234,2.1690792135,2.141851552,1.8329883345,1.7671215515,1.7914611555,1.932135893,1.7546384225,1.907355815,1.9898289285,2.1742377565,1.9840210265,1.962424169,1.831221897,2.1261579565,1.961311631,1.9621834975,2.130907812,2.2669553005,2.029367162,1.955281222,1.989252225,1.9636093625,2.1358347655,2.072252091 +ATP1A4,2.1597164535,2.1784132505,2.006160208,2.0788399675,2.173944234,2.133156518,2.2444106655,2.1040814375,2.077415601,2.0989293605,2.3155495675,2.13273821,2.179091016,2.120310744,2.1883860755,2.1732987975,1.9519446925,2.113056096,2.1186079925,2.186947209,2.155898229,2.2650253775,2.1666411485,2.1806041675,2.243183292,2.099773184,2.132001942,2.1653086935,2.157179792,2.0530678565,2.1397375845,2.2485316185,2.1747839295,2.2118659705,2.159109076,2.0779357255,2.1786563775,2.1731785065 +ATP1B1,2.587808472,3.016742021,2.72979512,2.616016249,2.672337027,2.721129018,2.7956942215,2.945600609,2.4297454045,3.246349299,2.711935723,2.497889518,2.82525256,2.7684993655,2.708045935,2.6566358605,2.901382345,2.996133179,2.9522244775,2.965350744,2.8496814845,2.622377623,2.7510413865,3.226499382,2.556587267,2.7003855385,2.375631984,3.0880533925,2.767180015,2.5406122055,2.6143764615,2.5263455125,2.6529237945,2.607797426,2.4389733755,2.757161525,2.632491527,3.031663606 +ATP1B2,2.9478226835,2.8951063715,2.7116414775,2.8646488995,2.8027233395,2.680583952,3.3322171975,2.9433380705,2.651983489,2.7525209375,2.834740951,2.8828842215,3.2849392685,2.796103798,2.759417326,2.9919243185,2.895197627,2.7613220505,2.7588769785,3.1203288775,2.666504587,2.901857409,2.7846065215,2.9525465,3.247675256,2.759156158,2.6396223025,2.9592873345,2.729229917,2.7083589975,3.1500840085,3.5423267045,2.867405758,2.6781220565,2.763456423,3.019648644,2.591369278,3.1328739435 +ATP1B3,3.498402855,3.3773869425,3.724579683,3.686111374,3.5325167765,3.4781442995,3.2292121095,3.5066199175,3.303012694,3.6509976375,3.1035850265,3.301351798,3.5201747925,3.608355236,3.2280512425,3.279850114,3.4753357135,3.493938918,3.5575305635,3.640637154,3.4057210505,3.230390457,3.459131586,3.791396783,3.3600879435,3.416749435,3.425139296,3.621513613,3.6266018655,3.6064146265,3.5027386015,3.1433606165,3.289114878,3.5019557935,3.4929166625,3.680634043,3.4267739835,3.707079142 +ATP1B4,1.414480093,1.343562185,1.3193082325,1.4185918905,1.3620864685,1.3661346815,1.3649901605,1.3108373645,1.435060275,1.328676348,1.441715452,1.432891337,1.4325522195,1.376626123,1.282735427,1.3706185215,1.3937832985,1.3244844505,1.2710108685,1.324617735,1.2233706875,1.412398645,1.42093327,1.424709653,1.34449928,1.30587799,1.415197611,1.410221671,1.360955424,1.341478174,1.466636389,1.432400146,1.3947118445,1.410950291,1.375967657,1.35148781,1.4601454535,1.490116605 +ATP23,2.22767072,2.173964832333333,2.3070875566666667,2.2182690826666667,2.2595994336666667,2.1148510750000002,2.1872788186666665,2.1278179636666668,2.218607610333333,2.205760706,2.0590068936666666,2.028050911,2.314689427333333,2.0884844966666667,2.1613928726666667,1.9737001503333333,2.248893293,2.2243438909999997,2.0902866323333336,2.3271289976666667,2.2238384886666664,2.1834032999999997,2.0159625633333333,2.3315221116666667,2.0832678183333333,2.0955799010000002,2.14776794,2.2027341970000003,2.246402167,2.3143234746666668,2.2153543063333334,2.0900713129999997,2.207815136666667,2.381769285333333,2.2306599266666667,2.2405975149999997,2.254386928,2.278140844333333 +ATP2A1,2.4896950715,2.5776105005,2.4496656025,2.5531008225,2.421259877,2.4719600075,2.5598110395,2.477189082,2.522009723,2.4065579345,2.5938193445,2.523226835,2.538115531,2.5114678565,2.521340554,2.599416054,2.4647101265,2.522664324,2.441106636,2.5322403405,2.555592539,2.529049831,2.516067911,2.608480512,2.487784109,2.481021664,2.5183340255,2.456637374,2.4977236015,2.5502346365,2.6274934375,2.5834590175,2.5305216835,2.326571372,2.5990615525,2.5092964915,2.492441984,2.4366686415 +ATP2A2,4.3280314865,4.2707103005,4.4683372645,4.372471673,4.284690597,4.389498451,4.0117494705,4.3133166825,4.376785058,4.4041146635,4.120422118,3.9739740795,4.1921721915,4.41820834,4.1680095905,4.199054386,4.349218654,4.3190108735,4.3638146925,4.296039982,4.2008036535,4.076906612,4.420670588,4.450958308,4.3372230055,4.2651738755,4.3156534085,4.4210985,4.4960160525,4.482285243,4.237768685,4.0102886755,4.311026314,4.1753734425,4.2473802515,4.273896701,4.261317963,4.331862347 +ATP2A3,4.1618609125,4.3979096025,4.652921371,4.475809766,4.729777132,4.3523791005,4.1418739095,4.3077906085,4.342938518,4.284916139,4.320337095,4.449058036,4.553696277,4.343143303,4.8492040005,4.484941726,4.2391216815,4.2672355395,4.360820515,4.4493822905,4.228232134,4.5481644485,4.693899694,4.5939621105,4.285476981,4.3789281235,4.301019457,4.2854457535,4.409937236,4.513840738,4.4043831655,4.379958638,4.540535966,3.667413752,4.56555382,4.4711212355,4.328428461,4.413693483 +ATP2B1,4.275079186,4.0907836645,4.313164497,4.138050118,4.2044182775,4.4316412895,3.8699689665,4.496669249,4.3612679335,4.6490104915,4.1847311965,3.84198394,4.085427998,4.170420321,3.804571506,4.1211553665,4.4012976175,4.530089974,4.1554157925,4.1778801175,4.1616470795,3.9840717165,4.098644435,4.1518643785,4.2549252955,4.2331647285,4.0543170085,4.5295120535,4.4175865835,4.1351932395,4.1051040935,3.92601402,4.2683619445,4.482924213,4.065097088,4.3665058775,4.3307074375,4.259795673 +ATP2B2,1.1476379252,1.1508716386,1.1062877194,1.1421933024,1.1235286806,1.1344716494,1.225734686,1.1425280382,1.1236381930000001,1.1150342426,1.1682448412,1.1623332412,1.1677716652,1.1278864452000001,1.183863996,1.1641171364,1.1016943434,1.12295876,1.1356149979999999,1.1590970956,1.1615717374,1.170813007,1.1391081718,1.1416777772,1.1240778418,1.1650407048,1.142061356,1.1287347862000001,1.1033273464,1.108334353,1.1725446976,1.1741758386,1.1605681016,1.09754201,1.1495597628,1.1310120524,1.1652362184,1.1550695184 +ATP2B3,0.67009420775,0.69039503075,0.653375204125,0.67278309675,0.67984287275,0.68630111075,0.697348059,0.658162984375,0.696814320375,0.646061541625,0.71728536275,0.697782262625,0.681406582875,0.6667302115,0.67310440575,0.729190075375,0.664259219,0.675232725375,0.648521516,0.662676096,0.663044502875,0.707622875375,0.661668965125,0.68755667675,0.679244140125,0.67536959475,0.688651632125,0.662864291375,0.662526680125,0.670015719,0.712184049,0.706549590875,0.693841264625,0.68635906925,0.6905666635,0.6642227205,0.678728598625,0.6756843945 +ATP2B4,2.16313740825,2.3086257355,2.135487492,2.220512329,2.17216531675,2.3432992455,2.1956367465,2.265385762,2.3514580515,2.39323442225,2.17405639325,2.16019321725,2.15767083825,2.23023948275,2.2811439135,2.13231267725,2.299734663,2.2429557775,2.2403705515,2.14205188725,2.18534641675,2.186298146,2.3305583365,2.294708343,2.2301097205,2.29643335225,2.23521153825,2.329789632,2.361718318,2.28371541275,2.07416568075,2.13263068275,2.3191009805,2.0764054475,2.25690913475,2.2396933595,2.261704386,2.30664385125 +ATP2C1,0.45005778826666665,0.44774351219999997,0.4472894668,0.4368213489333333,0.4450544792666667,0.46442527493333335,0.4077224616,0.4562321277333333,0.46060655,0.509594658,0.41715576260000004,0.41510510393333333,0.4342922484,0.4497745181333333,0.43247360006666663,0.42881000733333335,0.4601326353333333,0.448932687,0.4470202729333333,0.4450785999333334,0.4333283346,0.4044653250666667,0.4377370964,0.47817419513333337,0.4275070508,0.44053537153333333,0.4353335056666667,0.4678445446,0.45540825046666666,0.44540978626666666,0.4160188708,0.3989521939333333,0.4489986752666667,0.4746344860666667,0.43019949566666665,0.4742958294,0.44534940079999996,0.46184272693333334 +ATP2C2,2.39242457,2.412078096,2.3866468435,2.3987708145,2.374747635,2.3110339845,2.4532625785,2.378370283,2.407450626,2.2717203215,2.466675631,2.4719509465,2.4152049435,2.3682625665,2.367993654,2.540227049,2.3355017715,2.4280299855,2.274628182,2.386296922,2.357427188,2.4962105545,2.311816769,2.392641279,2.3788108495,2.43594588,2.4314909505,2.387823687,2.3347137635,2.360937404,2.5257608405,2.4237944445,2.3896907275,2.3806196855,2.4184977795,2.323045878,2.3981125595,2.294104507 +ATP4A,2.7470056905,2.7553255495,2.6729818805,2.7797360305,2.714518621,2.7298307765,2.887866398,2.737907365,2.815733149,2.7317560905,2.8331930375,2.7533793835,2.84061627,2.7154291485,2.7946067805,2.8851063975,2.719278005,2.6969469885,2.746159829,2.771861649,2.7477762115,2.849666206,2.745531978,2.739502826,2.713743119,2.839736362,2.743122989,2.658518938,2.684710571,2.7131241735,2.923507731,2.9632849935,2.7855007125,2.732676615,2.81420375,2.733166428,2.709606426,2.652066766 +ATP4B,2.611979112,2.572064065,2.6700427785,2.7219485875,2.583529486,2.598157782,2.8636280495,2.7211524525,2.634010918,2.4903005005,2.7390844365,2.7185528295,2.626417852,2.599674229,2.5873369215,2.812118003,2.660857972,2.686271575,2.654975919,2.7079927605,2.592592047,2.8110900265,2.571428642,2.642612545,2.700386658,2.577287646,2.708905493,2.5401929135,2.6871382095,2.621661189,2.787621742,2.7870409125,2.655874822,2.6291981455,2.7572434285,2.555248387,2.641266495,2.5522566535 +ATP5F1A,2.29853031325,2.314479134,2.41779151525,2.38671507875,2.323707912,2.33216963075,2.13199719175,2.41946099775,2.3428031805,2.33001885625,2.29841299825,2.231080218,2.354212814,2.30497060475,2.19429490275,2.342602487,2.35764047875,2.3781285265,2.4089714545,2.18653270175,2.2380944395,2.27946418775,2.221176416,2.320892758,2.2452684235,2.37870090675,2.35453650325,2.357848617,2.385275362,2.39273214275,2.2870001515,2.251813468,2.34099620225,2.1109943375,2.31822994525,2.2941198385,2.37615121275,2.301805119 +ATP5F1B,1.7737554333333332,1.609604733,1.7816490399999998,1.7543472016666666,1.7718391766666668,1.7338793683333333,1.8140203033333335,1.7502262899999999,1.6920656833333334,1.7230462199999999,1.7283143216666668,1.74034593,1.7455392616666667,1.7382694516666666,1.67289322,1.7270646583333333,1.75828428,1.736646265,1.7307648716666666,1.7451852216666666,1.6140822835,1.7491446,1.71931518,1.786756455,1.7449260566666667,1.77656214,1.7108900766666666,1.770098,1.768192465,1.7787627933333334,1.7668981400000001,1.8200164383333333,1.7450683733333332,1.5688692596666665,1.73272284,1.7719630883333333,1.7178335966666667,1.7799252900000002 +ATP5F1C,2.325885821,2.1499604775,2.2755019065,2.33323516625,2.29447782875,2.31587647475,2.16941407575,2.34449646125,2.26476824075,2.32604192425,2.33602941625,2.14950465575,2.304677621,2.31725018425,2.2212283825,2.262443366,2.35037046825,2.25346711725,2.3571528235,2.2609822735,2.09727678225,2.26745797975,2.12835205475,2.311538779,2.20032664275,2.21293082025,2.26842302225,2.26201495925,2.34852831925,2.384663301,2.32885543075,2.1733708395,2.22391832575,2.3643139805,2.356920582,2.3383051815,2.3248847765,2.32392649825 +ATP5F1D,2.00580057875,1.97098502875,2.14670763675,2.0823201845,2.1705740515,2.004244537,2.05189565675,2.120450317,2.00759109275,1.9886130655,2.0705646075,2.106740806,2.128681708,2.03597997675,2.196334135,2.16081778775,2.09639567875,2.06681908475,2.04103424775,1.9974146025,1.91438245175,2.06906481775,2.16868562825,2.115567709,2.10452119,2.0557947785,2.0138944185,2.05833816575,2.07934498875,2.17801064075,2.12372653975,1.9953332455,2.09819048825,1.7590670155,2.06904260475,2.09235513625,2.05345797225,2.081575173 +ATP5F1E,3.5129060381999997,3.6092430249999996,3.6166126106,3.7567887868,3.8409941736,3.2840474116,3.5330368188,3.8474804596,3.5920936614,3.6624341013999997,3.5913362604,3.6972858044000003,3.6086932566000005,3.550468489,3.588447535,3.6912639661999997,3.6457114502000003,3.6765947485999995,3.7218983182,3.6384827937999997,3.3760320098000003,3.7005068668,3.6400988224,3.6718925854,3.5450802168,3.480590475,3.4113663897999995,3.5914149886,3.6932992614,3.527515626,3.8585437626,3.5773351006,3.8115028568,3.0599670571999997,3.7320626464,3.6836426268,3.7293666074000003,3.7859863127999995 +ATP5F1EP2,1.3640104581999999,1.537011081,1.2794123126,1.5329681088,1.4172750736,1.3929516151999999,1.5293208828,1.5187610296,1.5021456674,1.4046847854,1.4574701304,1.5670181664,1.4377882346,1.361896499,1.3647032769999998,1.5570151802,1.4058146482,1.3917283886,1.3929227442,1.3968006438,1.427207885,1.5575935788000002,1.4302745244000001,1.3989057894,1.3790562008,1.4095329250000002,1.3397664098,1.4194727426,1.5251450414,1.449277172,1.5700366606,1.4681727786,1.5395524247999999,1.5118869434,1.5222042224,1.4530874668,1.4253769154,1.4627906668 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+CHMP2A,5.34664386,4.63060513,5.27727384,5.482533795,5.237829915,5.19035518,5.200287655,5.23512756,5.026455105,5.23580434,5.304078165,5.191317925,5.30233379,5.297100655,4.7681972705,5.237362165,5.24582306,5.299152765,5.33789276,5.219558735,4.9857915685,5.271675,5.002665955,5.31890907,5.158464915,5.236404685,5.206300965,5.279368015,5.46091464,5.295247005,5.36335128,5.375130175,5.314453475,5.16678361,5.26264531,5.33384006,5.16369313,5.220606275 +CHMP2B,3.365374379,3.0692957425,3.6262009805,3.540162216,3.6106843155,3.453907108,3.003881763,3.381359789,3.3099001995,3.8586084075,3.0968976175,3.152407855,3.4378736215,3.4338712595,3.0137961125,3.365311129,3.6330548075,3.479412062,3.417084518,3.415488701,3.252239317,2.994446828,2.899223688,3.632701189,3.1073191635,3.2720147565,3.2253053675,3.5721281375,3.495587846,3.53407787,3.307557959,2.849068784,3.4265460825,3.678707875,3.392770973,3.658465477,3.5299205845,3.701706684 +CHMP4A,1.83390332925,1.72221858375,1.94584628275,1.8905786315,1.85940485525,1.83925351325,1.69392119075,1.83922852525,1.8141073705,1.88074451,1.73542884625,1.83447249775,1.91049675325,1.842699065,1.8176038095,1.83624121975,1.8979860955,1.84715679475,1.8846723495,1.77015395825,1.72419895125,1.756959433,1.77357238325,1.8594961405,1.71561047325,1.82436500075,1.8341961255,1.84116366025,1.8870223735,1.986975201,1.7378932865,1.688781223,1.81675780075,1.8056886145,1.81543490925,1.8679310075,1.8329947475,1.848413198 +CHMP4B,7.6524049195,6.839000765,7.810557135,7.842188628,7.814033468,7.4236407645,7.369234328,7.9425933755,7.7076695525000005,7.681247496999999,7.1794970355,7.288212044,7.8722769745,7.7013350015,7.2816550819999994,7.398431712000001,7.670781825,7.913107106,7.390131974500001,7.607690689,7.4802752214999995,7.442513563,7.697772704,7.6944611135,7.8008787055,7.543013248499999,7.3161165685,7.630622788,7.959113027,7.7237414829999995,7.5676179165,7.282067405499999,7.6457619415,7.487037165,7.4303240885,7.3631584065,7.7699587695000005,7.444386761500001 +CHMP4C,2.6688477765,2.949197446,2.739825138,2.6657186175,2.9674843655,2.7652890275,2.996261144,2.8065824415,2.915500137,2.713930631,2.8869530215,2.8736268235,2.792848592,2.986799027,3.115159159,2.917029229,2.877134113,2.8749126495,2.993484985,2.9417481445,2.8433605665,3.090321644,2.7249250765,2.7020535795,2.874538604,2.8999235025,2.734449545,2.748371326,2.7583701935,2.6824846285,2.8628337255,2.840828919,2.92327396,2.7542420115,2.9334826575,2.748658702,2.862687757,2.806161313 +CHMP5,4.812074443,4.37656676925,5.3503890905,4.63194832925,4.7071532,4.692264664750001,4.325169510249999,4.6189375644999995,4.34812055,4.7954883975,4.59641265625,4.793465192999999,5.005372009749999,4.4537640375,4.7910426712500005,4.415103044,4.69162897875,4.4350244320000005,4.6121398115,4.8880751257499995,4.4889882355,4.45462262,4.386188319,4.8126032495,4.5383881615,4.0885439315,4.5838624997499995,4.63905444125,4.74432755525,5.13083913775,4.72770090625,4.2828672582500005,4.7128710645,4.29355755825,4.657935167,5.188589632,4.64216187075,4.8331568785000005 +CHMP6,3.3264730385,3.2149308985,3.630041474,3.575139479,3.6191094295,3.2212954005,3.338627015,3.4420207635,3.3926860735,3.322552401,3.1830495805,3.5252689685,3.5098412595,3.4583110125,3.6843267995,3.4432989225,3.358178037,3.3123533715,3.3784180115,3.3061432775,3.26855091,3.4527553045,3.712727331,3.5974661905,3.316962741,3.435492588,3.38381205,3.2810562905,3.4726724435,3.6247188635,3.498225748,3.2943149535,3.4570732255,2.8169582465,3.4992928975,3.432412202,3.450490974,3.2932343525 +CHMP7,2.735043437333333,2.5565960116666666,2.769082032,2.565052101,2.6909356696666666,2.683332330666667,2.483125073,2.630676057666667,2.669692528666667,2.7218825196666665,2.512979730666667,2.7399793066666667,2.744835362,2.7436969613333333,2.7464128103333336,2.765407275333333,2.677446027666667,2.692450033666667,2.667267204333333,2.6111095253333336,2.5645031253333332,2.6159437156666665,2.664727002333333,2.751766451,2.4747162953333333,2.714618249666667,2.679400722,2.730057633,2.696158248,2.7944424436666666,2.4678763663333334,2.538746799,2.6894264126666667,2.3987894796666667,2.7976342106666667,2.7406358026666666,2.6684592376666667,2.5728953999999997 +CHN1,2.1440020975,2.1477437385,1.9600054075,1.8922862375,2.1022028415,2.1418823375,2.2237382715,2.192273789,2.1762586615,2.243547845,2.089491824,2.019275712,2.2284681275,2.003803726,1.986399312,1.963304297,2.356754471,2.2012916235,2.1796013935,2.241646054,2.125433246,2.009618019,1.855157958,2.1839085165,1.829390318,2.060455324,2.062730369,2.405153282,2.1154583905,1.935310206,1.9788982915,1.961016,2.062023559,2.665259342,2.0610384425,2.1875706755,2.233332202,2.176628374 +CHN2,0.26524821172413793,0.2387395157586207,0.25581168903448276,0.266392008862069,0.2668979644137931,0.24847042686206897,0.24615221617241378,0.27170827120689656,0.26903993455172415,0.28157970372413793,0.2621390774827586,0.2404426508965517,0.26162527155172416,0.2602895331724138,0.23138337203448275,0.2562247952413793,0.270374494137931,0.26105864513793103,0.27295284168965517,0.2530720103103448,0.2599709343448276,0.2536373046551724,0.2607793084137931,0.2707638630689655,0.25209874558620693,0.2605415884137931,0.26042398955172413,0.2732574006896552,0.27623299913793103,0.2692823694482759,0.2641578327586207,0.22961529020689656,0.26441636113793104,0.26882647672413795,0.26313853737931037,0.2605491551034483,0.24733961668965518,0.2710495054137931 +CHODL,0.500368779125,0.514601350625,0.50458538725,0.510767518125,0.519679204,0.498731349875,0.508565039125,0.47590607225,0.47219679375,0.467298176625,0.4948018235,0.512956326625,0.480379383125,0.5013211615,0.488102486125,0.5024312715,0.48650700425,0.45638068475,0.4806376675,0.51091221975,0.49001366975,0.504919544375,0.50431869275,0.4864062965,0.522132644375,0.485622134125,0.523851464875,0.4808028735,0.515015210875,0.49956166725,0.493203502,0.50659536625,0.52558952175,0.498014841875,0.500950075875,0.479686036125,0.485967256,0.53287216125 +CHORDC1,3.1838450816000003,2.7473300628,3.7707035462,2.8683514839999997,2.5659155868666668,3.0652453569333336,2.9941406796666667,2.8966076508,3.2013286100666667,3.7633393025333333,3.2661045547333334,3.4348712598,3.4867279414,2.9970086551333335,3.2291585815333335,3.1624200481333333,3.8348533846000006,3.1093728810666668,2.9401573919999997,3.4659190408666665,3.3949708231333333,2.4946885294666665,2.355412769,3.608581268,2.777722150133333,2.694083616,3.1396436926666667,3.671040568266667,3.394570079933333,3.6889563043999996,2.470790078533333,3.755925655266667,2.699543063466667,3.1723017916,2.3017762802,3.3519360415333335,3.161959513333333,3.186249913 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+CHPF2,2.6475960466666666,2.583001606333333,2.6602440856666667,2.662826246333333,2.7507763546666664,2.625084255,2.650855329666667,2.6301323536666668,2.5417729403333333,2.6431896983333334,2.499973268,2.725722827666667,2.655559814,2.7752740350000003,2.872276774,2.716064639666667,2.603879965,2.5630692173333336,2.6533049086666667,2.6498704136666666,2.5190358716666665,2.6933092706666666,2.8327256356666664,2.7884980513333333,2.659279223,2.612670741666667,2.625955498,2.6569925026666668,2.7172300723333334,2.823705304,2.681931586333333,2.536273093,2.7194314453333335,2.226644685333333,2.707771231666667,2.690766508333333,2.519224224333333,2.6846862456666667 +CHPT1,5.0984059366666665,4.6668598113333335,4.861645286666667,4.790921881166667,4.9072558226666665,4.938871772166666,5.128449557833334,4.834445276333333,4.540034681666667,4.842239175333333,4.556479959333333,4.793140503166667,5.131594529499999,4.572384116166667,4.4184414225,4.626379343166667,4.9933862305000005,4.8239795029999994,4.742367855,5.024983387,4.849015687833333,4.936266438833333,4.5017448416666666,4.909543867833333,4.7927395175,4.583043766,4.729076698333333,4.995999944166666,4.897968527333333,4.8102083926666666,5.038490152166666,5.259152597166667,4.8750083405,5.1639678245,4.465744074666667,4.811803164333334,4.929810994666666,5.09903567 +CHRAC1,3.863706237,3.746196747,3.965512451,3.925628675,4.255100579,3.856517296,4.139595086,3.7721691805,3.769772867,4.036765667,3.6788560955,3.953191582,3.9780718905,4.0101040285,3.6827492555,3.9779523325,4.117736405,4.021686636,4.014952229,3.97582787,3.77190725,3.81096681,3.715819591,4.051887327,4.018928075,3.9975908815,3.9530512265,4.1586566055,4.1323438195,3.905711354,3.876593722,3.706470105,3.947825697,3.755318855,3.914621136,3.987954431,4.0815650025,4.0380760075 +CHRD,0.4471147753571429,0.4566125778571429,0.4414907713571429,0.4485920910714286,0.44473298064285716,0.4438540126428571,0.48262137392857146,0.45054793021428574,0.44245941421428575,0.4328270994285714,0.4597411475,0.4664698528571428,0.4568243960714286,0.44525015714285715,0.4579005055,0.4628834671428571,0.4405013294285714,0.4489949690714286,0.4468741952857143,0.4533716187857143,0.4411050052142857,0.47836089785714286,0.44903121599999996,0.45409787507142857,0.44692757714285714,0.4600127117857143,0.446451095,0.4387337982857143,0.44004132314285715,0.4442703490714286,0.47165456042857146,0.4667994515,0.4519329459285714,0.4369115672142857,0.4646523163571428,0.44355661442857147,0.452995969,0.4397994574285714 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+CLGN,1.1901601475,1.2090671725,1.173764542,1.183995273,1.2087763765,1.181505002,1.438690243,1.2177170305,1.1589233735,1.209104183,1.193485796,1.305003406,1.210040017,1.2826385525,1.1970217295,1.151216808,1.115737905,1.2533610415,1.2515690375,1.2543380775,1.196595723,1.241840354,1.247475674,1.377574246,1.2105937295,1.1048654875,1.152888419,1.192381967,1.235491936,1.175378765,1.231380051,1.226064235,1.1748277355,1.3533289395,1.2807041535,1.2037174345,1.210589099,1.1801852255 +CLHC1,1.4287133235,1.453677984,1.3730287805,1.5422337005,1.366747841,1.426008646,1.411316227,1.2968274235,1.3329981655,1.4887142835,1.294108911,1.407089736,1.2862439015,1.4194510125,1.5110487195,1.1704665625,1.4338524135,1.3771043095,1.4090615845,1.406126415,1.3490843485,1.307056634,1.4998603325,1.548809525,1.597838889,1.3048519165,1.4339682165,1.4672616845,1.332871877,1.392225557,1.2596485175,1.2985940805,1.263216152,1.4012136795,1.3057115335,1.3679647515,1.3876735935,1.48639151 +CLIC1,4.600428013,4.2283998825,4.6196037405,4.990343279,4.81729171,4.6366142115,4.3676417545,4.7165966945,4.6211511075,4.8532455395,4.6661197995,4.5246651405,4.718645767,4.768277684,4.686095099,4.7203295545,4.684891128,4.7038027355,4.762996438,4.579242663,4.3871583335,4.699639774,4.6818858305,4.8491359405,4.6804920025,4.6591029925,4.345723205,4.6904479175,4.8772671885,4.9935430135,4.8726318995,4.408227828,4.8385826705,4.4024672895,4.6057115045,4.7721744025,4.5412944195,4.811599826 +CLIC2,1.68247736875,1.05606302925,1.47167659725,1.243466697,1.42167932875,1.32426746475,2.05793242225,1.500025874,0.8917777005,1.5770004595,1.03638825425,1.55463642475,1.619282505,1.2502335735,1.1055414925,1.2492516125,1.767636765,1.178044393,1.2438778735,1.479141777,1.188566335,1.5112001,0.970341902,1.5171721995,1.59994849225,1.05121034475,1.1094239325,1.8036327615,1.27508238175,1.1523793235,1.49204565475,1.880469174,1.63323115325,1.3420458435,1.17413433625,1.3193610705,1.127551959,1.90714455225 +CLIC3,2.940611792,3.27954035,3.3005415075,3.060554262,3.308822613,3.241039175,3.259698661,3.2960855105,3.3028036075,3.136567653,3.1649518965,3.4798612685,3.399084963,3.1865782575,3.5407694525,3.268403732,3.1742154655,3.054538649,3.115970949,3.217307718,3.173451678,3.4049204635,3.350005512,3.3407943255,3.351866958,3.350261632,3.1511966475,3.029759003,3.33084222,3.2113437725,3.286030302,3.2847359795,3.2678457555,2.9437299995,3.2004266415,3.2738874525,3.235359631,3.1387976775 +CLIC4,13.056889136575,13.080255819008334,13.144587010625001,13.427720612058334,13.834192735258334,12.915565914183334,13.494210135933333,13.226115146358334,12.852913481358332,13.308506347641666,13.322436790833333,13.334230885775,13.392830746958333,13.223851422391666,13.191789649533334,13.69390115395,13.087004482041667,13.324363327033332,13.23011662995,13.434444717533333,12.648290041108334,13.517525609983332,13.193848947466666,13.381295339016667,13.029749102108333,13.122330849908332,13.061798326158334,13.0698395546,13.1789640599,13.33895456495,13.537618900783333,13.17181628935,13.458390001975,12.59785158825,13.293739396791665,13.313092579058333,13.234640712616667,13.376350472975002 +CLIC5,5.446889262,6.186051384500001,5.324078655499999,5.2309384535,6.1080655995,5.7968412695,5.4568013505,5.6078942355,5.911561974,5.7770262685,5.5033848034999995,5.853570335500001,5.2178768479999995,5.575993347,5.904278648,5.6122507415,5.864585174,5.975426624500001,5.40214198,5.3620370479999995,5.331554178,5.558877848,5.2962701244999995,5.894989220499999,5.113522979000001,5.537308937500001,5.611253743000001,5.54996805,5.577112997,5.6072957475,5.4308241245,4.99814531,5.8540511665,6.67347827,5.996984448,6.3374132095,5.600343018,5.7679693565 +CLIC6,2.2338853225,2.4248629695,2.2425262975,2.248498312,2.3065236965,2.1116377235,2.317591523,2.1846969055,2.1192410895,2.09309335,2.152219753,2.218436482,2.2760987035,2.218378837,2.3303369145,2.348356632,2.170422758,2.202811706,2.338477501,2.2268638535,2.110810301,2.1832861625,2.171768875,2.163902075,2.2209500645,2.277674073,2.243446192,2.0515355145,2.038996091,2.3349867225,2.3861209225,2.2215387055,2.263437173,2.1867176205,2.176240722,2.2855134945,2.2543428965,2.195734324 +CLINT1,2.6935435363333333,2.6053129264166666,2.6862695545,2.6799231255833336,2.7464486803333332,2.6836368926666667,2.5132138213333333,2.72016173075,2.6874755810833335,2.7773778123333335,2.5756280985833335,2.5125811995000005,2.6587537618333332,2.719602452416667,2.4972549248333333,2.7153438463333335,2.7354061735000004,2.6769388024999996,2.6874209085833334,2.6783050350833335,2.69699192425,2.59902426975,2.5135562658333335,2.8662557434166667,2.575857448,2.6204796955833336,2.5811630762499997,2.71631508775,2.6979244031666667,2.731440433583333,2.6489778660833334,2.5590339465,2.628443357916667,2.803499975833333,2.7070474888333336,2.7360186486666667,2.6491687152499996,2.7262596424166667 +CLIP1,2.427543798,2.2002921216666667,2.372607265666667,2.415299014,2.2958000326666665,2.426585419,2.194022287,2.4053220426666666,2.346576568,2.533386756,2.357694467,2.1327386876666665,2.2891686116666667,2.355879514666667,2.148788857,2.221605204333333,2.438458983333333,2.3600468483333334,2.3473651236666666,2.4166044953333334,2.353551406333333,2.19119318,2.2548367636666664,2.5181757719999998,2.269055011333333,2.263650902333333,2.3247995686666667,2.4034219323333335,2.460437135333333,2.4701045543333335,2.2971916213333334,2.2618670516666666,2.3710931186666664,2.380154585,2.3020330596666665,2.4086683696666666,2.3219954916666667,2.4357785703333334 +CLIP2,2.238616855,2.1675377516666665,2.2995590213333332,2.385796443333333,2.4643492306666666,2.1984420373333333,2.331642371,2.260811888,2.142415777,2.3548431869999997,2.2572219583333335,2.2983761903333333,2.2949294056666667,2.4176085703333334,2.4861331410000003,2.2602137653333334,2.255044278666667,2.2835100223333336,2.362626968333333,2.2971478236666667,2.151511122,2.2665215153333333,2.4736854813333333,2.403717367,2.362739879333333,2.2970776356666667,2.202876409,2.278487015,2.3130560483333333,2.3247835196666666,2.3613513806666666,2.2763874833333335,2.3206332826666665,2.0786103766666666,2.271990063,2.257119397333333,2.2796771563333333,2.3049295180000002 +CLIP3,2.1110643073333333,2.1773467256666668,2.114046346333333,2.149885966,2.17103599,2.070718144666667,2.2538515896666667,2.1280386886666665,2.1142590676666666,2.011774615333333,2.141964063,2.2375232513333336,2.2038935706666667,2.058758474,2.1767236603333333,2.2746643533333333,2.0975038483333335,2.059928755,2.076916333666667,2.1455605746666664,2.0470320133333333,2.1435969729999997,2.1953839366666665,2.1874446830000003,2.1533664973333333,2.1867931793333333,2.1885658753333335,2.069971002,2.1283790603333332,2.2135108889999997,2.2041049943333335,2.1375788976666668,2.2026868376666666,1.990714827,2.2260106680000002,2.1103914993333333,2.0706831103333334,2.0884434026666665 +CLIP4,2.422721860333333,2.3607964356666664,2.435998709666667,2.425638301333333,2.3811359506666667,2.519940002,2.144189702333333,2.5076696513333334,2.4596531433333335,2.604145801,2.3855466816666664,2.196342129,2.3017977573333335,2.553236898,2.3234424676666667,2.328935197333333,2.4425561436666667,2.5642842223333333,2.560449558333333,2.353678872666667,2.364304153,2.1301660743333333,2.4040200966666667,2.414443552333333,2.4240783403333332,2.380428373,2.42958349,2.528359473,2.4454655206666667,2.4416153313333333,2.1938711806666666,2.2011492803333335,2.4465895273333333,2.474664858666667,2.424037975666667,2.445586615333333,2.389734031666667,2.498414937 +CLK1,0.6751916981666667,0.6837407224166667,0.7006958710000001,0.6607200794166667,0.6698355378333334,0.7128113645833333,0.6008312853333333,0.677604639,0.6731136250833334,0.7321622370833333,0.6015234025,0.6534192765,0.67691854775,0.7080070040833334,0.6675491075000001,0.64034726175,0.7083344256666666,0.65585184075,0.6807471176666667,0.6978804103333333,0.6798055660000001,0.6106868338333333,0.6169946094166666,0.6720715025833334,0.634604107,0.6359225895,0.6968209708333334,0.7025773105,0.67226229475,0.67418727925,0.6463378259166667,0.6236033091666667,0.673000645,0.7082940955833333,0.6665501630833334,0.7269583792500001,0.6829637195,0.6997712694166666 +CLK2,0.8297173682000001,0.8154848807,0.8261610997,0.8572577982,0.8690724892,0.8292609204,0.8279614739,0.8209304831,0.829664416,0.8976613724,0.8023792155,0.8370586588,0.8463740067,0.8564232718,0.8617559955999999,0.8361613082,0.8373409232,0.8479546849,0.8533137979,0.8534182621999999,0.8053082742000001,0.8285594475,0.8544083623000001,0.8748722791000001,0.8428424035000001,0.8393839868,0.8432417716,0.8682956480999999,0.8534265824,0.8556249558,0.8242264885999999,0.8238585522999999,0.8721783933999999,0.788068885,0.8763560425,0.8544629055999999,0.8310351599000001,0.8278577799000001 +CLK2P1,0.8297173682000001,0.8154848807,0.8261610997,0.8572577982,0.8690724892,0.8292609204,0.8279614739,0.8209304831,0.829664416,0.8976613724,0.8023792155,0.8370586588,0.8463740067,0.8564232718,0.8617559955999999,0.8361613082,0.8373409232,0.8479546849,0.8533137979,0.8534182621999999,0.8053082742000001,0.8285594475,0.8544083623000001,0.8748722791000001,0.8428424035000001,0.8393839868,0.8432417716,0.8682956480999999,0.8534265824,0.8556249558,0.8242264885999999,0.8238585522999999,0.8721783933999999,0.788068885,0.8763560425,0.8544629055999999,0.8310351599000001,0.8278577799000001 +CLK3,0.6032257845625,0.5608930479375,0.593022081875,0.581273049625,0.597265483,0.58316092525,0.645469756875,0.5841355433125,0.56486002925,0.5781543910625,0.5571822315,0.5813040276875,0.593004805625,0.5790503724375,0.5768314375,0.5795055473125,0.606201593,0.578845763625,0.576639963875,0.5793917301875,0.574415194625,0.594781347875,0.586455506,0.589728341375,0.597800465875,0.566536322125,0.5659530093125,0.5949989045625,0.5930634205,0.592955531375,0.590989814625,0.629056310625,0.598438908875,0.566071568875,0.5745171558125,0.5941061514375,0.561573420875,0.6127217734375 +CLK4,2.4058386803333334,2.365412113,2.446645660666667,2.320972362,2.253395975,2.3195603793333333,2.084191118,2.3777395426666668,2.36500771,2.5669691906666667,2.0919261776666667,2.196961227,2.158368180666667,2.283208683666667,2.297591235666667,2.2592138086666664,2.381833989,2.2949420533333336,2.354345229,2.369156425,2.2683632706666668,2.180986842333333,2.213137293,2.4107296413333335,2.2287684,2.1241645226666668,2.2530085730000002,2.382955155,2.267773183,2.478307081666667,2.025477049,2.052537219,2.369122262,2.390262922666667,2.3689048613333332,2.4255439433333335,2.271009347,2.3166914359999997 +CLMN,3.425503125,3.187365423,3.5258326415,3.761906267,3.3912832135,3.345861692,3.348854308,3.5037487925,3.59079488,3.671660565,3.365603494,3.224246752,3.330265787,3.5143234905,3.116531467,3.421190144,3.6683765135,3.7211405095,3.5894986565,3.321315762,3.527331671,3.3218111345,3.458970256,3.5946205365,3.7189590525,3.2779683895,3.3064727635,3.664531695,3.5199783425,3.429425145,3.6206844055,3.223082017,3.488060897,3.3565917425,3.303423268,3.3855869445,3.3395127505,3.352310633 +CLMP,2.4804806675,2.4409443775,2.41650424,2.338994464,2.3662318875,2.3460336435,2.30978712,2.402274853,2.380480974,2.3025903465,2.508998539,2.4382718535,2.4130634465,2.409156439,2.420702204,2.549450772,2.3566750175,2.391886387,2.382306494,2.3837889365,2.344896093,2.355927078,2.3619195495,2.3697885875,2.323577584,2.4458723765,2.344761733,2.3339278095,2.367809012,2.299468858,2.4862163115,2.5384690525,2.514136393,2.2907040845,2.341738625,2.3552373615,2.3271067825,2.449459798 +CLN5,1.1106203102,1.0165919902,1.2623443617999999,1.176196202,1.1366262682000001,1.0971968814,0.9966867246,1.066212225,1.0888593480000002,1.1557930666,1.0278405138,1.0910271066,1.1193437524,1.0985451795999999,1.053106852,1.1310212566,1.1122808320000002,1.1913174830000002,1.11222817,1.1377619984,1.0374062986,1.0559596822,1.0293871402,1.2280919342,1.0230132168000001,1.0265306781999999,1.0930991358,1.0856737874,1.1671401562,1.2021150182,1.0982345932,0.9569514044,1.0937528716,1.1260201781999999,1.0858281416,1.256660186,1.1305600096,1.1084056318 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+NBPF22P,1.5572595478,1.4792409458,1.3626667666,1.4630032294,1.6220133086,1.5938299454,1.3896111908,1.4614079414,1.340725082,1.340169352,1.5409152884000001,1.3929359734,1.4231400109999999,1.437128501,1.4264985088,1.387398942,1.3206082715999998,1.4005479353999999,1.5215432284000001,1.5732007288,1.483404709,1.457952038,1.1292974118,1.6958111484,1.4178457908,1.7507022317999998,1.4293473205999998,1.336885695,1.4070823094,1.2768653157999998,1.4497681951999999,1.4943474526,1.4446982104000001,1.7122431956,1.6092916938000001,1.3030119758,1.3654521736,1.3972290163999999 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