{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "ff56af5d", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.549459Z", "iopub.status.busy": "2025-03-25T06:01:22.549360Z", "iopub.status.idle": "2025-03-25T06:01:22.709396Z", "shell.execute_reply": "2025-03-25T06:01:22.709072Z" } }, "outputs": [], "source": [ "import sys\n", "import os\n", "sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '../..')))\n", "\n", "# Path Configuration\n", "from tools.preprocess import *\n", "\n", "# Processing context\n", "trait = \"Osteoporosis\"\n", "cohort = \"GSE35925\"\n", "\n", "# Input paths\n", "in_trait_dir = \"../../input/GEO/Osteoporosis\"\n", "in_cohort_dir = \"../../input/GEO/Osteoporosis/GSE35925\"\n", "\n", "# Output paths\n", "out_data_file = \"../../output/preprocess/Osteoporosis/GSE35925.csv\"\n", "out_gene_data_file = \"../../output/preprocess/Osteoporosis/gene_data/GSE35925.csv\"\n", "out_clinical_data_file = \"../../output/preprocess/Osteoporosis/clinical_data/GSE35925.csv\"\n", "json_path = \"../../output/preprocess/Osteoporosis/cohort_info.json\"\n" ] }, { "cell_type": "markdown", "id": "918bd136", "metadata": {}, "source": [ "### Step 1: Initial Data Loading" ] }, { "cell_type": "code", "execution_count": 2, "id": "41cdb303", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.710805Z", "iopub.status.busy": "2025-03-25T06:01:22.710662Z", "iopub.status.idle": "2025-03-25T06:01:22.830585Z", "shell.execute_reply": "2025-03-25T06:01:22.830249Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background Information:\n", "!Series_title\t\"Calcitriol supplementation effects on Ki67 expression and transcriptional profile of breast cancer specimens from post-menopausal patients\"\n", "!Series_summary\t\"Background: Breast cancer patients present lower 1,25(OH)2D3 or 25(OH)D3 serum levels than unaffected women. Although 1,25(OH)2D3 pharmacological concentrations of 1,25(OH)2D3 may exert antiproliferative effects in breast cancer cell lines, much uncertainty remains about the effects of calcitriol supplementation in tumor specimens in vivo. We have evaluated tumor dimension (ultrassonography), proliferative index (Ki67 expression), 25(OH)D3 serum concentration and gene expression profile, before and after a short term calcitriol supplementation (dose to prevent osteoporosis) to post-menopausal patients. Results: Thirty three patients with operable disease had tumor samples evaluated. Most of them (87.5%) presented 25(OH)D3 insufficiency (<30 ng/mL). Median period of calcitriol supplementation was 30 days. Although tumor dimension did not vary, Ki67 immunoexpression decreased after supplementation. Transcriptional analysis of 15 matched pre/post-supplementation samples using U133 Plus 2.0 GeneChip (Affymetrix) revealed 18 genes over-expressed in post-supplementation tumors. As a technical validation procedure, expression of four genes was also determined by RT-qPCR and a direct correlation was observed between both methods (microarray vs PCR). To further explore the effects of near physiological concentrations of calcitriol on breast cancer samples, an ex vivo model of fresh tumor slices was utilized. Tumor samples from another 12 post-menopausal patients were sliced and treated in vitro with slightly high concentrations of calcitriol (0.5nM), that can be attained in vivo, for 24 hours In this model, expression of PBEF1, EGR1, ATF3, FOS and RGS1 was not induced after a short exposure to calcitriol. Conclusions: In our work, most post-menopausal breast cancer patients presented at least 25(OH)D3 insufficiency. In these patients, a short period of calcitriol supplementation may prevent tumor growth and reduce Ki67 expression, probably associated with discrete transcriptional changes. This observation deserves further investigation to better clarify calcitriol effects in tumor behavior under physiological conditions.\"\n", "!Series_overall_design\t\"Post-menopausal patients with early stage breast cancer, in the absence of distant metastasis, were invited to take part in the study. This protocol was approved by the Institutional Ethics Committee, and a written informed consent was signed by all participants. Patients had blood and tumor samples collected during biopsy, and were prescribed calcitriol supplementation, (Rocaltrol)TM 0.50 ug/day PO, as recommended for osteoporosis prevention. Tumor specimens obtained during biopsy (pre-supplementation) or breast surgery (post-supplementation) were hand dissected and samples with at least 70% tumor cells were further processed. Breast surgery followed in about one month\"\n", "Sample Characteristics Dictionary:\n", "{0: ['gender: female'], 1: ['age: 54', 'age: 62', 'age: 63', 'age: 49', 'age: 66', 'age: 56', 'age: 52', 'age: 51', 'age: 64'], 2: ['histologic type: metaplastic', 'histologic type: CDI', 'histologic type: CLI', 'histologic type: CDI/CLI', 'histologic type: CDICLI'], 3: ['tissue type: breast cancer']}\n" ] } ], "source": [ "from tools.preprocess import *\n", "# 1. Identify the paths to the SOFT file and the matrix file\n", "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n", "\n", "# 2. Read the matrix file to obtain background information and sample characteristics data\n", "background_prefixes = ['!Series_title', '!Series_summary', '!Series_overall_design']\n", "clinical_prefixes = ['!Sample_geo_accession', '!Sample_characteristics_ch1']\n", "background_info, clinical_data = get_background_and_clinical_data(matrix_file, background_prefixes, clinical_prefixes)\n", "\n", "# 3. Obtain the sample characteristics dictionary from the clinical dataframe\n", "sample_characteristics_dict = get_unique_values_by_row(clinical_data)\n", "\n", "# 4. Explicitly print out all the background information and the sample characteristics dictionary\n", "print(\"Background Information:\")\n", "print(background_info)\n", "print(\"Sample Characteristics Dictionary:\")\n", "print(sample_characteristics_dict)\n" ] }, { "cell_type": "markdown", "id": "2a479f6c", "metadata": {}, "source": [ "### Step 2: Dataset Analysis and Clinical Feature Extraction" ] }, { "cell_type": "code", "execution_count": 3, "id": "1fdc8658", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.831859Z", "iopub.status.busy": "2025-03-25T06:01:22.831747Z", "iopub.status.idle": "2025-03-25T06:01:22.837089Z", "shell.execute_reply": "2025-03-25T06:01:22.836814Z" } }, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 1. Gene Expression Data Availability\n", "# Based on the background information, this dataset contains transcriptional analysis (U133 Plus 2.0 GeneChip)\n", "# which suggests gene expression data is available\n", "is_gene_available = True\n", "\n", "# 2. Variable Availability and Data Type Conversion\n", "# 2.1 Data Availability\n", "\n", "# For trait: From the background information, these are breast cancer samples \n", "# No direct mention of osteoporosis in patients, only that calcitriol is used at doses to prevent osteoporosis\n", "# Since everyone has breast cancer (tissue type: breast cancer), there's no variation in trait status\n", "trait_row = None # No variation in trait status for osteoporosis\n", "\n", "# For age: Age information is available in row 1\n", "age_row = 1\n", "\n", "# For gender: All patients are female as mentioned in row 0\n", "gender_row = 0 # However, this is constant (all female)\n", "\n", "# 2.2 Data Type Conversion\n", "\n", "# Since trait data is not available for osteoporosis, we create a placeholder function\n", "def convert_trait(value):\n", " return None\n", "\n", "# Age conversion function - ages are numeric values\n", "def convert_age(value):\n", " try:\n", " # Extract the value after the colon and convert to float\n", " return float(value.split(': ')[1].strip())\n", " except:\n", " return None\n", "\n", "# Gender conversion function - converting female to 0, male to 1\n", "def convert_gender(value):\n", " try:\n", " gender = value.split(': ')[1].strip().lower()\n", " if gender == 'female':\n", " return 0\n", " elif gender == 'male':\n", " return 1\n", " else:\n", " return None\n", " except:\n", " return None\n", "\n", "# 3. Save Metadata\n", "# Trait data is not available for osteoporosis\n", "is_trait_available = trait_row is not None\n", "validate_and_save_cohort_info(\n", " is_final=False, \n", " cohort=cohort, \n", " info_path=json_path, \n", " is_gene_available=is_gene_available, \n", " is_trait_available=is_trait_available\n", ")\n", "\n", "# 4. Clinical Feature Extraction\n", "# Since trait_row is None, we skip this substep\n" ] }, { "cell_type": "markdown", "id": "7d7a4f79", "metadata": {}, "source": [ "### Step 3: Gene Data Extraction" ] }, { "cell_type": "code", "execution_count": 4, "id": "3d469adc", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.838119Z", "iopub.status.busy": "2025-03-25T06:01:22.838020Z", "iopub.status.idle": "2025-03-25T06:01:22.985925Z", "shell.execute_reply": "2025-03-25T06:01:22.985556Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Index(['1007_s_at', '1053_at', '117_at', '121_at', '1255_g_at', '1294_at',\n", " '1316_at', '1320_at', '1405_i_at', '1431_at', '1438_at', '1487_at',\n", " '1494_f_at', '1552256_a_at', '1552257_a_at', '1552258_at', '1552261_at',\n", " '1552263_at', '1552264_a_at', '1552266_at'],\n", " dtype='object', name='ID')\n" ] } ], "source": [ "# 1. Use the get_genetic_data function from the library to get the gene_data from the matrix_file previously defined.\n", "gene_data = get_genetic_data(matrix_file)\n", "\n", "# 2. Print the first 20 row IDs (gene or probe identifiers) for future observation.\n", "print(gene_data.index[:20])\n" ] }, { "cell_type": "markdown", "id": "a187d77d", "metadata": {}, "source": [ "### Step 4: Gene Identifier Review" ] }, { "cell_type": "code", "execution_count": 5, "id": "5100935d", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.987234Z", "iopub.status.busy": "2025-03-25T06:01:22.987115Z", "iopub.status.idle": "2025-03-25T06:01:22.988956Z", "shell.execute_reply": "2025-03-25T06:01:22.988688Z" } }, "outputs": [], "source": [ "# These identifiers appear to be Affymetrix probe IDs (like '1007_s_at', '1053_at'), not human gene symbols.\n", "# Affymetrix probe IDs need to be mapped to gene symbols for biological interpretation.\n", "\n", "requires_gene_mapping = True\n" ] }, { "cell_type": "markdown", "id": "947ddffc", "metadata": {}, "source": [ "### Step 5: Gene Annotation" ] }, { "cell_type": "code", "execution_count": 6, "id": "9b083ae6", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:22.990160Z", "iopub.status.busy": "2025-03-25T06:01:22.990049Z", "iopub.status.idle": "2025-03-25T06:01:25.903078Z", "shell.execute_reply": "2025-03-25T06:01:25.902713Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gene annotation preview:\n", "{'ID': ['1007_s_at', '1053_at', '117_at', '121_at', '1255_g_at'], 'GB_ACC': ['U48705', 'M87338', 'X51757', 'X69699', 'L36861'], 'SPOT_ID': [nan, nan, nan, nan, nan], 'Species Scientific Name': ['Homo sapiens', 'Homo sapiens', 'Homo sapiens', 'Homo sapiens', 'Homo sapiens'], 'Annotation Date': ['Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014', 'Oct 6, 2014'], 'Sequence Type': ['Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence', 'Exemplar sequence'], 'Sequence Source': ['Affymetrix Proprietary Database', 'GenBank', 'Affymetrix Proprietary Database', 'GenBank', 'Affymetrix Proprietary Database'], 'Target Description': ['U48705 /FEATURE=mRNA /DEFINITION=HSU48705 Human receptor tyrosine kinase DDR gene, complete cds', 'M87338 /FEATURE= /DEFINITION=HUMA1SBU Human replication factor C, 40-kDa subunit (A1) mRNA, complete cds', \"X51757 /FEATURE=cds /DEFINITION=HSP70B Human heat-shock protein HSP70B' gene\", 'X69699 /FEATURE= /DEFINITION=HSPAX8A H.sapiens Pax8 mRNA', 'L36861 /FEATURE=expanded_cds /DEFINITION=HUMGCAPB Homo sapiens guanylate cyclase activating protein (GCAP) gene exons 1-4, complete cds'], 'Representative Public ID': ['U48705', 'M87338', 'X51757', 'X69699', 'L36861'], 'Gene Title': ['discoidin domain receptor tyrosine kinase 1 /// microRNA 4640', 'replication factor C (activator 1) 2, 40kDa', \"heat shock 70kDa protein 6 (HSP70B')\", 'paired box 8', 'guanylate cyclase activator 1A (retina)'], 'Gene Symbol': ['DDR1 /// MIR4640', 'RFC2', 'HSPA6', 'PAX8', 'GUCA1A'], 'ENTREZ_GENE_ID': ['780 /// 100616237', '5982', '3310', '7849', '2978'], 'RefSeq Transcript ID': ['NM_001202521 /// NM_001202522 /// NM_001202523 /// NM_001954 /// NM_013993 /// NM_013994 /// NR_039783 /// XM_005249385 /// XM_005249386 /// XM_005249387 /// XM_005249389 /// XM_005272873 /// XM_005272874 /// XM_005272875 /// XM_005272877 /// XM_005275027 /// XM_005275028 /// XM_005275030 /// XM_005275031 /// XM_005275162 /// XM_005275163 /// XM_005275164 /// XM_005275166 /// XM_005275457 /// XM_005275458 /// XM_005275459 /// XM_005275461 /// XM_006715185 /// XM_006715186 /// XM_006715187 /// XM_006715188 /// XM_006715189 /// XM_006715190 /// XM_006725501 /// XM_006725502 /// XM_006725503 /// XM_006725504 /// XM_006725505 /// XM_006725506 /// XM_006725714 /// XM_006725715 /// XM_006725716 /// XM_006725717 /// XM_006725718 /// XM_006725719 /// XM_006725720 /// XM_006725721 /// XM_006725722 /// XM_006725827 /// XM_006725828 /// XM_006725829 /// XM_006725830 /// XM_006725831 /// XM_006725832 /// XM_006726017 /// XM_006726018 /// XM_006726019 /// XM_006726020 /// XM_006726021 /// XM_006726022 /// XR_427836 /// XR_430858 /// XR_430938 /// XR_430974 /// XR_431015', 'NM_001278791 /// NM_001278792 /// NM_001278793 /// NM_002914 /// NM_181471 /// XM_006716080', 'NM_002155', 'NM_003466 /// NM_013951 /// NM_013952 /// NM_013953 /// NM_013992', 'NM_000409 /// XM_006715073'], 'Gene Ontology Biological Process': ['0001558 // regulation of cell growth // inferred from electronic annotation /// 0001952 // regulation of cell-matrix adhesion // inferred from electronic annotation /// 0006468 // protein phosphorylation // inferred from electronic annotation /// 0007155 // cell adhesion // traceable author statement /// 0007169 // transmembrane receptor protein tyrosine kinase signaling pathway // inferred from electronic annotation /// 0007565 // female pregnancy // inferred from electronic annotation /// 0007566 // embryo implantation // inferred from electronic annotation /// 0007595 // lactation // inferred from electronic annotation /// 0008285 // negative regulation of cell proliferation // inferred from electronic annotation /// 0010715 // regulation of extracellular matrix disassembly // inferred from mutant phenotype /// 0014909 // smooth muscle cell migration // inferred from mutant phenotype /// 0016310 // phosphorylation // inferred from electronic annotation /// 0018108 // peptidyl-tyrosine phosphorylation // inferred from electronic annotation /// 0030198 // extracellular matrix organization // traceable author statement /// 0038063 // collagen-activated tyrosine kinase receptor signaling pathway // inferred from direct assay /// 0038063 // collagen-activated tyrosine kinase receptor signaling pathway // inferred from mutant phenotype /// 0038083 // peptidyl-tyrosine autophosphorylation // inferred from direct assay /// 0043583 // ear development // inferred from electronic annotation /// 0044319 // wound healing, spreading of cells // inferred from mutant phenotype /// 0046777 // protein autophosphorylation // inferred from direct assay /// 0060444 // branching involved in mammary gland duct morphogenesis // inferred from electronic annotation /// 0060749 // mammary gland alveolus development // inferred from electronic annotation /// 0061302 // smooth muscle cell-matrix adhesion // inferred from mutant phenotype', '0000278 // mitotic cell cycle // traceable author statement /// 0000722 // telomere maintenance via recombination // traceable author statement /// 0000723 // telomere maintenance // traceable author statement /// 0006260 // DNA replication // traceable author statement /// 0006271 // DNA strand elongation involved in DNA replication // traceable author statement /// 0006281 // DNA repair // traceable author statement /// 0006283 // transcription-coupled nucleotide-excision repair // traceable author statement /// 0006289 // nucleotide-excision repair // traceable author statement /// 0006297 // nucleotide-excision repair, DNA gap filling // traceable author statement /// 0015979 // photosynthesis // inferred from electronic annotation /// 0015995 // chlorophyll biosynthetic process // inferred from electronic annotation /// 0032201 // telomere maintenance via semi-conservative replication // traceable author statement', '0000902 // cell morphogenesis // inferred from electronic annotation /// 0006200 // ATP catabolic process // inferred from direct assay /// 0006950 // response to stress // inferred from electronic annotation /// 0006986 // response to unfolded protein // traceable author statement /// 0034605 // cellular response to heat // inferred from direct assay /// 0042026 // protein refolding // inferred from direct assay /// 0070370 // cellular heat acclimation // inferred from mutant phenotype', '0001655 // urogenital system development // inferred from sequence or structural similarity /// 0001656 // metanephros development // inferred from electronic annotation /// 0001658 // branching involved in ureteric bud morphogenesis // inferred from expression pattern /// 0001822 // kidney development // inferred from expression pattern /// 0001823 // mesonephros development // inferred from sequence or structural similarity /// 0003337 // mesenchymal to epithelial transition involved in metanephros morphogenesis // inferred from expression pattern /// 0006351 // transcription, DNA-templated // inferred from direct assay /// 0006355 // regulation of transcription, DNA-templated // inferred from electronic annotation /// 0007275 // multicellular organismal development // inferred from electronic annotation /// 0007417 // central nervous system development // inferred from expression pattern /// 0009653 // anatomical structure morphogenesis // traceable author statement /// 0030154 // cell differentiation // inferred from electronic annotation /// 0030878 // thyroid gland development // inferred from expression pattern /// 0030878 // thyroid gland development // inferred from mutant phenotype /// 0038194 // thyroid-stimulating hormone signaling pathway // traceable author statement /// 0039003 // pronephric field specification // inferred from sequence or structural similarity /// 0042472 // inner ear morphogenesis // inferred from sequence or structural similarity /// 0042981 // regulation of apoptotic process // inferred from sequence or structural similarity /// 0045893 // positive regulation of transcription, DNA-templated // inferred from direct assay /// 0045893 // positive regulation of transcription, DNA-templated // inferred from sequence or structural similarity /// 0045944 // positive regulation of transcription from RNA polymerase II promoter // inferred from direct assay /// 0048793 // pronephros development // inferred from sequence or structural similarity /// 0071371 // cellular response to gonadotropin stimulus // inferred from direct assay /// 0071599 // otic vesicle development // inferred from expression pattern /// 0072050 // S-shaped body morphogenesis // inferred from electronic annotation /// 0072073 // kidney epithelium development // inferred from electronic annotation /// 0072108 // positive regulation of mesenchymal to epithelial transition involved in metanephros morphogenesis // inferred from sequence or structural similarity /// 0072164 // mesonephric tubule development // inferred from electronic annotation /// 0072207 // metanephric epithelium development // inferred from expression pattern /// 0072221 // metanephric distal convoluted tubule development // inferred from sequence or structural similarity /// 0072278 // metanephric comma-shaped body morphogenesis // inferred from expression pattern /// 0072284 // metanephric S-shaped body morphogenesis // inferred from expression pattern /// 0072289 // metanephric nephron tubule formation // inferred from sequence or structural similarity /// 0072305 // negative regulation of mesenchymal cell apoptotic process involved in metanephric nephron morphogenesis // inferred from sequence or structural similarity /// 0072307 // regulation of metanephric nephron tubule epithelial cell differentiation // inferred from sequence or structural similarity /// 0090190 // positive regulation of branching involved in ureteric bud morphogenesis // inferred from sequence or structural similarity /// 1900212 // negative regulation of mesenchymal cell apoptotic process involved in metanephros development // inferred from sequence or structural similarity /// 1900215 // negative regulation of apoptotic process involved in metanephric collecting duct development // inferred from sequence or structural similarity /// 1900218 // negative regulation of apoptotic process involved in metanephric nephron tubule development // inferred from sequence or structural similarity /// 2000594 // positive regulation of metanephric DCT cell differentiation // inferred from sequence or structural similarity /// 2000611 // positive regulation of thyroid hormone generation // inferred from mutant phenotype /// 2000612 // regulation of thyroid-stimulating hormone secretion // inferred from mutant phenotype', '0007165 // signal transduction // non-traceable author statement /// 0007601 // visual perception // inferred from electronic annotation /// 0007602 // phototransduction // inferred from electronic annotation /// 0007603 // phototransduction, visible light // traceable author statement /// 0016056 // rhodopsin mediated signaling pathway // traceable author statement /// 0022400 // regulation of rhodopsin mediated signaling pathway // traceable author statement /// 0030828 // positive regulation of cGMP biosynthetic process // inferred from electronic annotation /// 0031282 // regulation of guanylate cyclase activity // inferred from electronic annotation /// 0031284 // positive regulation of guanylate cyclase activity // inferred from electronic annotation /// 0050896 // response to stimulus // inferred from electronic annotation'], 'Gene Ontology Cellular Component': ['0005576 // extracellular region // inferred from electronic annotation /// 0005615 // extracellular space // inferred from direct assay /// 0005886 // plasma membrane // traceable author statement /// 0005887 // integral component of plasma membrane // traceable author statement /// 0016020 // membrane // inferred from electronic annotation /// 0016021 // integral component of membrane // inferred from electronic annotation /// 0043235 // receptor complex // inferred from direct assay /// 0070062 // extracellular vesicular exosome // inferred from direct assay', '0005634 // nucleus // inferred from electronic annotation /// 0005654 // nucleoplasm // traceable author statement /// 0005663 // DNA replication factor C complex // inferred from direct assay', '0005737 // cytoplasm // inferred from direct assay /// 0005814 // centriole // inferred from direct assay /// 0005829 // cytosol // inferred from direct assay /// 0008180 // COP9 signalosome // inferred from direct assay /// 0070062 // extracellular vesicular exosome // inferred from direct assay /// 0072562 // blood microparticle // inferred from direct assay', '0005634 // nucleus // inferred from direct assay /// 0005654 // nucleoplasm // inferred from sequence or structural similarity /// 0005730 // nucleolus // inferred from direct assay', '0001750 // photoreceptor outer segment // inferred from electronic annotation /// 0001917 // photoreceptor inner segment // inferred from electronic annotation /// 0005578 // proteinaceous extracellular matrix // inferred from electronic annotation /// 0005886 // plasma membrane // inferred from direct assay /// 0016020 // membrane // inferred from electronic annotation /// 0097381 // photoreceptor disc membrane // traceable author statement'], 'Gene Ontology Molecular Function': ['0000166 // nucleotide binding // inferred from electronic annotation /// 0004672 // protein kinase activity // inferred from electronic annotation /// 0004713 // protein tyrosine kinase activity // inferred from electronic annotation /// 0004714 // transmembrane receptor protein tyrosine kinase activity // traceable author statement /// 0005515 // protein binding // inferred from physical interaction /// 0005518 // collagen binding // inferred from direct assay /// 0005518 // collagen binding // inferred from mutant phenotype /// 0005524 // ATP binding // inferred from electronic annotation /// 0016301 // kinase activity // inferred from electronic annotation /// 0016740 // transferase activity // inferred from electronic annotation /// 0016772 // transferase activity, transferring phosphorus-containing groups // inferred from electronic annotation /// 0038062 // protein tyrosine kinase collagen receptor activity // inferred from direct assay /// 0046872 // metal ion binding // inferred from electronic annotation', '0000166 // nucleotide binding // inferred from electronic annotation /// 0003677 // DNA binding // inferred from electronic annotation /// 0005515 // protein binding // inferred from physical interaction /// 0005524 // ATP binding // inferred from electronic annotation /// 0016851 // magnesium chelatase activity // inferred from electronic annotation /// 0017111 // nucleoside-triphosphatase activity // inferred from electronic annotation', '0000166 // nucleotide binding // inferred from electronic annotation /// 0005524 // ATP binding // inferred from electronic annotation /// 0019899 // enzyme binding // inferred from physical interaction /// 0031072 // heat shock protein binding // inferred from physical interaction /// 0042623 // ATPase activity, coupled // inferred from direct assay /// 0051082 // unfolded protein binding // inferred from direct assay', '0000979 // RNA polymerase II core promoter sequence-specific DNA binding // inferred from direct assay /// 0003677 // DNA binding // inferred from direct assay /// 0003677 // DNA binding // inferred from mutant phenotype /// 0003700 // sequence-specific DNA binding transcription factor activity // inferred from direct assay /// 0004996 // thyroid-stimulating hormone receptor activity // traceable author statement /// 0005515 // protein binding // inferred from physical interaction /// 0044212 // transcription regulatory region DNA binding // inferred from direct assay', '0005509 // calcium ion binding // inferred from electronic annotation /// 0008048 // calcium sensitive guanylate cyclase activator activity // inferred from electronic annotation /// 0030249 // guanylate cyclase regulator activity // inferred from electronic annotation /// 0046872 // metal ion binding // inferred from electronic annotation']}\n" ] } ], "source": [ "# 1. Use the 'get_gene_annotation' function from the library to get gene annotation data from the SOFT file.\n", "gene_annotation = get_gene_annotation(soft_file)\n", "\n", "# 2. Use the 'preview_df' function from the library to preview the data and print out the results.\n", "print(\"Gene annotation preview:\")\n", "print(preview_df(gene_annotation))\n" ] }, { "cell_type": "markdown", "id": "72d8b863", "metadata": {}, "source": [ "### Step 6: Gene Identifier Mapping" ] }, { "cell_type": "code", "execution_count": 7, "id": "130d0db5", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:25.904439Z", "iopub.status.busy": "2025-03-25T06:01:25.904314Z", "iopub.status.idle": "2025-03-25T06:01:26.087594Z", "shell.execute_reply": "2025-03-25T06:01:26.087222Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "After mapping, first 20 gene symbols:\n", "Index(['A1BG', 'A1BG-AS1', 'A1CF', 'A2M', 'A2M-AS1', 'A2ML1', 'A2MP1',\n", " 'A4GALT', 'A4GNT', 'AA06', 'AAAS', 'AACS', 'AACSP1', 'AADAC', 'AADACL2',\n", " 'AADACP1', 'AADAT', 'AAED1', 'AAGAB', 'AAK1'],\n", " dtype='object', name='Gene')\n" ] } ], "source": [ "# 1. Identify columns for gene mapping\n", "# Looking at the data, 'ID' contains identifiers like '1007_s_at' which match gene_data's index\n", "# 'Gene Symbol' contains gene symbols like 'DDR1 /// MIR4640'\n", "prob_col = 'ID'\n", "gene_col = 'Gene Symbol'\n", "\n", "# 2. Get the gene mapping dataframe using the get_gene_mapping function\n", "gene_mapping = get_gene_mapping(gene_annotation, prob_col, gene_col)\n", "\n", "# 3. Convert probe-level measurements to gene expression data using apply_gene_mapping function\n", "# This will divide probe measurements equally among mapped genes\n", "gene_data = apply_gene_mapping(gene_data, gene_mapping)\n", "\n", "# Print the first 20 rows to verify the transformation from probe IDs to gene symbols\n", "print(\"After mapping, first 20 gene symbols:\")\n", "print(gene_data.index[:20])\n" ] }, { "cell_type": "markdown", "id": "48f31769", "metadata": {}, "source": [ "### Step 7: Data Normalization and Linking" ] }, { "cell_type": "code", "execution_count": 8, "id": "be7d6722", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T06:01:26.088929Z", "iopub.status.busy": "2025-03-25T06:01:26.088818Z", "iopub.status.idle": "2025-03-25T06:01:26.495031Z", "shell.execute_reply": "2025-03-25T06:01:26.494639Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Normalized gene data saved to ../../output/preprocess/Osteoporosis/gene_data/GSE35925.csv\n", "No trait data available for osteoporosis in this dataset.\n", "Dataset determined to be unusable for osteoporosis analysis and linked data was not saved\n" ] } ], "source": [ "# 1. Normalize the obtained gene data with the 'normalize_gene_symbols_in_index' function from the library.\n", "normalized_gene_data = normalize_gene_symbols_in_index(gene_data)\n", "os.makedirs(os.path.dirname(out_gene_data_file), exist_ok=True)\n", "normalized_gene_data.to_csv(out_gene_data_file)\n", "print(f\"Normalized gene data saved to {out_gene_data_file}\")\n", "\n", "# Check if trait_row is None (no trait data available)\n", "if trait_row is None:\n", " # If no trait data available, mark dataset as unusable for trait study\n", " print(\"No trait data available for osteoporosis in this dataset.\")\n", " \n", " # Use is_final=False for cases where trait data is not available\n", " validate_and_save_cohort_info(\n", " is_final=False, \n", " cohort=cohort, \n", " info_path=json_path, \n", " is_gene_available=True, \n", " is_trait_available=False\n", " )\n", " \n", " print(\"Dataset determined to be unusable for osteoporosis analysis and linked data was not saved\")\n", "else:\n", " # This block won't be executed for this dataset, but included for completeness\n", " clinical_features_df = geo_select_clinical_features(\n", " clinical_data, \n", " trait=trait, \n", " trait_row=trait_row, \n", " convert_trait=convert_trait,\n", " age_row=age_row,\n", " convert_age=convert_age,\n", " gender_row=gender_row,\n", " convert_gender=convert_gender\n", " )\n", "\n", " # Save the clinical data\n", " os.makedirs(os.path.dirname(out_clinical_data_file), exist_ok=True)\n", " clinical_features_df.to_csv(out_clinical_data_file)\n", " print(f\"Clinical data saved to {out_clinical_data_file}\")\n", "\n", " # Link the clinical and genetic data\n", " linked_data = geo_link_clinical_genetic_data(clinical_features_df, normalized_gene_data)\n", " print(\"Linked data shape:\", linked_data.shape)\n", "\n", " # Handle missing values in the linked data\n", " linked_data = handle_missing_values(linked_data, trait)\n", "\n", " # Determine whether the trait and demographic features are severely biased\n", " is_trait_biased, unbiased_linked_data = judge_and_remove_biased_features(linked_data, trait)\n", "\n", " # Conduct quality check and save the cohort information\n", " is_usable = validate_and_save_cohort_info(\n", " is_final=True, \n", " cohort=cohort, \n", " info_path=json_path, \n", " is_gene_available=True, \n", " is_trait_available=True, \n", " is_biased=is_trait_biased, \n", " df=unbiased_linked_data,\n", " note=\"Contains gene expression data from breast cancer patients with trait information.\"\n", " )\n", "\n", " # Save linked data if it's usable\n", " if is_usable:\n", " os.makedirs(os.path.dirname(out_data_file), exist_ok=True)\n", " unbiased_linked_data.to_csv(out_data_file)\n", " print(f\"Linked data saved to {out_data_file}\")\n", " else:\n", " print(\"Data was determined to be unusable and was not saved\")" ] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 5 }