{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "5a5987d4", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.041771Z", "iopub.status.busy": "2025-03-25T08:21:55.041591Z", "iopub.status.idle": "2025-03-25T08:21:55.203259Z", "shell.execute_reply": "2025-03-25T08:21:55.202918Z" } }, "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 = \"Chronic_obstructive_pulmonary_disease_(COPD)\"\n", "cohort = \"GSE64593\"\n", "\n", "# Input paths\n", "in_trait_dir = \"../../input/GEO/Chronic_obstructive_pulmonary_disease_(COPD)\"\n", "in_cohort_dir = \"../../input/GEO/Chronic_obstructive_pulmonary_disease_(COPD)/GSE64593\"\n", "\n", "# Output paths\n", "out_data_file = \"../../output/preprocess/Chronic_obstructive_pulmonary_disease_(COPD)/GSE64593.csv\"\n", "out_gene_data_file = \"../../output/preprocess/Chronic_obstructive_pulmonary_disease_(COPD)/gene_data/GSE64593.csv\"\n", "out_clinical_data_file = \"../../output/preprocess/Chronic_obstructive_pulmonary_disease_(COPD)/clinical_data/GSE64593.csv\"\n", "json_path = \"../../output/preprocess/Chronic_obstructive_pulmonary_disease_(COPD)/cohort_info.json\"\n" ] }, { "cell_type": "markdown", "id": "abad30f0", "metadata": {}, "source": [ "### Step 1: Initial Data Loading" ] }, { "cell_type": "code", "execution_count": 2, "id": "65286817", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.204618Z", "iopub.status.busy": "2025-03-25T08:21:55.204480Z", "iopub.status.idle": "2025-03-25T08:21:55.371089Z", "shell.execute_reply": "2025-03-25T08:21:55.370775Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Background Information:\n", "!Series_title\t\"The Role of Interleukin-23 in the Early Development of Emphysema in HIV1+ Smokers [Affymetrix]\"\n", "!Series_summary\t\"Matrix metalloproteinase-9 (MMP-9) expression is up-regulated in alveolar macrophages (AM) of HIV1+ smokers who develop emphysema. Based on the knowledge that lung epithelial lining fluid (ELF) of HIV1+ smokers has increased levels of inflammatory cytokines compared to HIV1- smokers, we hypothesized up-regulation of lung cytokines in HIV1+ smokers may be functionally related to increased MMP-9 expression. Cytokine arrays evaluated cytokine protein levels in ELF obtained from 5 groups of individuals: HIV1‾ healthy nonsmokers, HIV1‾ healthy smokers, HIV1‾ smokers with low diffusing capacity (DLCO) , HIV1 + nonsmokers, and HIV1 + smokers with low DLCO. Among several pro-inflammatory cytokines elevated in ELF associated with smoking and HIV1+, increased levels of the Th17-related cytokine IL-23 were found in HIV1- smokers with low DLCO and HIV1+ smokers and nonsmokers. Relative IL-23 gene expression was significantly increased in AM of HIV1+ individuals, with greater expression in AM of HIV1+ smokers with low DLCO. Infection with HIV1 in vitro induced IL-23 expression in normal AM. Since AM purified by adherence contain a small number of lymphocytes, we hy-pothesized that in an AM/lymphocyte co-culture system, IL-23 would up-regulate MMP-9. IL-23 stimulation of AM/lymphocyte co-cultures in vitro induced increased MMP-9 mRNA levels and protein. AM of healthy individuals did not express IL-23 receptors (IL-23R), lung T lymphocytes express IL-23R and interact with AM in order to up-regulate MMP-9. This mechanism may contribute to the increased tissue destruction in the lungs of HIV1+ smokers and suggests that Th-17 related inflammation may play a role.\"\n", "!Series_summary\t\"IL-23 upregulates MMP-9 expression in human alveolar macrophages via a T lymphocyte/alveolar macrophage interaction, suggesting a possible role for Th-17 related inflammation in accelerated emphysema in HIV1+ smokers.\"\n", "!Series_overall_design\t\"Array-based expression profiling of alveolar macrophages from HIV1+ smokers and HIV1- smokers.\"\n", "Sample Characteristics Dictionary:\n", "{0: ['smoking status: smoker'], 1: ['disease state: HIV+', 'disease state: HIV-'], 2: ['cell type: alveolar macrophage']}\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": "9f5afa08", "metadata": {}, "source": [ "### Step 2: Dataset Analysis and Clinical Feature Extraction" ] }, { "cell_type": "code", "execution_count": 3, "id": "ddf66cf5", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.372223Z", "iopub.status.busy": "2025-03-25T08:21:55.372110Z", "iopub.status.idle": "2025-03-25T08:21:55.375306Z", "shell.execute_reply": "2025-03-25T08:21:55.375014Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "No COPD/emphysema trait data available for extraction.\n" ] } ], "source": [ "# 1. Gene Expression Data Analysis\n", "# Based on the background information, this dataset appears to be analyzing gene expression\n", "# specifically for MMP-9 in alveolar macrophages using Affymetrix arrays.\n", "is_gene_available = True\n", "\n", "# 2. Variable Availability and Data Type Conversion\n", "# For COPD/emphysema trait:\n", "# Looking at the sample characteristics, there's no direct mention of COPD, emphysema, or DLCO status\n", "# The study examines HIV+ smokers with low DLCO as having emphysema, but we don't have this info in the characteristics\n", "# We cannot reliably infer COPD status from just HIV status without DLCO measurements\n", "trait_row = None # No direct or reliably inferable COPD trait data\n", "\n", "# Age data - Not available in the sample characteristics\n", "age_row = None\n", "\n", "# Gender data - Not available in the sample characteristics\n", "gender_row = None\n", "\n", "# Conversion functions defined for completeness\n", "def convert_trait(value):\n", " return None # Not applicable since we don't have COPD trait data\n", "\n", "def convert_age(value):\n", " return None # Not used but included for completeness\n", "\n", "def convert_gender(value):\n", " return None # Not used but included for completeness\n", "\n", "# 3. Save Metadata\n", "# Determine trait data availability\n", "is_trait_available = trait_row is not None # Will be False\n", "\n", "# Initial filtering validation\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", "# Skip this step as trait_row is None (no reliable COPD trait data available)\n", "print(\"No COPD/emphysema trait data available for extraction.\")\n" ] }, { "cell_type": "markdown", "id": "d2e668b5", "metadata": {}, "source": [ "### Step 3: Gene Data Extraction" ] }, { "cell_type": "code", "execution_count": 4, "id": "42043d08", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.376353Z", "iopub.status.busy": "2025-03-25T08:21:55.376243Z", "iopub.status.idle": "2025-03-25T08:21:55.538484Z", "shell.execute_reply": "2025-03-25T08:21:55.538109Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matrix file found: ../../input/GEO/Chronic_obstructive_pulmonary_disease_(COPD)/GSE64593/GSE64593_series_matrix.txt.gz\n", "Gene data shape: (54675, 34)\n", "First 20 gene/probe identifiers:\n", "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. Get the SOFT and matrix file paths again \n", "soft_file, matrix_file = geo_get_relevant_filepaths(in_cohort_dir)\n", "print(f\"Matrix file found: {matrix_file}\")\n", "\n", "# 2. Use the get_genetic_data function from the library to get the gene_data\n", "try:\n", " gene_data = get_genetic_data(matrix_file)\n", " print(f\"Gene data shape: {gene_data.shape}\")\n", " \n", " # 3. Print the first 20 row IDs (gene or probe identifiers)\n", " print(\"First 20 gene/probe identifiers:\")\n", " print(gene_data.index[:20])\n", "except Exception as e:\n", " print(f\"Error extracting gene data: {e}\")\n" ] }, { "cell_type": "markdown", "id": "7cf0c5c8", "metadata": {}, "source": [ "### Step 4: Gene Identifier Review" ] }, { "cell_type": "code", "execution_count": 5, "id": "c9832ad8", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.539763Z", "iopub.status.busy": "2025-03-25T08:21:55.539653Z", "iopub.status.idle": "2025-03-25T08:21:55.541465Z", "shell.execute_reply": "2025-03-25T08:21:55.541194Z" } }, "outputs": [], "source": [ "# These identifiers like '1007_s_at', '1053_at', etc. are Affymetrix probe IDs\n", "# They are not human gene symbols and need to be mapped to gene symbols\n", "\n", "requires_gene_mapping = True\n" ] }, { "cell_type": "markdown", "id": "2434e9f3", "metadata": {}, "source": [ "### Step 5: Gene Annotation" ] }, { "cell_type": "code", "execution_count": 6, "id": "b2354645", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:55.542535Z", "iopub.status.busy": "2025-03-25T08:21:55.542438Z", "iopub.status.idle": "2025-03-25T08:21:58.961088Z", "shell.execute_reply": "2025-03-25T08:21:58.960751Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Gene annotation preview:\n", "Columns in gene annotation: ['ID', 'GB_ACC', 'SPOT_ID', 'Species Scientific Name', 'Annotation Date', 'Sequence Type', 'Sequence Source', 'Target Description', 'Representative Public ID', 'Gene Title', 'Gene Symbol', 'ENTREZ_GENE_ID', 'RefSeq Transcript ID', 'Gene Ontology Biological Process', 'Gene Ontology Cellular Component', 'Gene Ontology Molecular Function']\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", "\n", "Searching for platform information in SOFT file:\n", "!Series_platform_id = GPL570\n", "\n", "Searching for gene symbol information in SOFT file:\n", "Found references to gene symbols:\n", "!Platform_relation = Alternative to: GPL19918 (Gene symbol version, 10K)\n", "!Platform_relation = Alternative to: GPL20182 (Gene Symbol Version)\n", "#Gene Symbol = A gene symbol, when one is available (from UniGene).\n", "ID\tGB_ACC\tSPOT_ID\tSpecies Scientific Name\tAnnotation Date\tSequence Type\tSequence Source\tTarget Description\tRepresentative Public ID\tGene Title\tGene Symbol\tENTREZ_GENE_ID\tRefSeq Transcript ID\tGene Ontology Biological Process\tGene Ontology Cellular Component\tGene Ontology Molecular Function\n", "\n", "Checking for additional annotation files in the directory:\n", "[]\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. Analyze the gene annotation dataframe to identify which columns contain the gene identifiers and gene symbols\n", "print(\"\\nGene annotation preview:\")\n", "print(f\"Columns in gene annotation: {gene_annotation.columns.tolist()}\")\n", "print(preview_df(gene_annotation, n=5))\n", "\n", "# Let's look for platform information in the SOFT file to understand the annotation better\n", "print(\"\\nSearching for platform information in SOFT file:\")\n", "with gzip.open(soft_file, 'rt') as f:\n", " for i, line in enumerate(f):\n", " if '!Series_platform_id' in line:\n", " print(line.strip())\n", " break\n", " if i > 100: # Limit search to first 100 lines\n", " print(\"Platform ID not found in first 100 lines\")\n", " break\n", "\n", "# Check if the SOFT file includes any reference to gene symbols\n", "print(\"\\nSearching for gene symbol information in SOFT file:\")\n", "with gzip.open(soft_file, 'rt') as f:\n", " gene_symbol_lines = []\n", " for i, line in enumerate(f):\n", " if 'GENE_SYMBOL' in line or 'gene_symbol' in line.lower() or 'symbol' in line.lower():\n", " gene_symbol_lines.append(line.strip())\n", " if i > 1000 and len(gene_symbol_lines) > 0: # Limit search but ensure we found something\n", " break\n", " \n", " if gene_symbol_lines:\n", " print(\"Found references to gene symbols:\")\n", " for line in gene_symbol_lines[:5]: # Show just first 5 matches\n", " print(line)\n", " else:\n", " print(\"No explicit gene symbol references found in first 1000 lines\")\n", "\n", "# Look for alternative annotation files or references in the directory\n", "print(\"\\nChecking for additional annotation files in the directory:\")\n", "all_files = os.listdir(in_cohort_dir)\n", "print([f for f in all_files if 'annotation' in f.lower() or 'platform' in f.lower() or 'gpl' in f.lower()])\n" ] }, { "cell_type": "markdown", "id": "2dac0b60", "metadata": {}, "source": [ "### Step 6: Gene Identifier Mapping" ] }, { "cell_type": "code", "execution_count": 7, "id": "92605ae1", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:58.962389Z", "iopub.status.busy": "2025-03-25T08:21:58.962272Z", "iopub.status.idle": "2025-03-25T08:21:59.167825Z", "shell.execute_reply": "2025-03-25T08:21:59.167507Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gene mapping dataframe shape: (45782, 2)\n", "Sample of gene mapping:\n", " ID Gene\n", "0 1007_s_at DDR1 /// MIR4640\n", "1 1053_at RFC2\n", "2 117_at HSPA6\n", "3 121_at PAX8\n", "4 1255_g_at GUCA1A\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Gene expression data shape after mapping: (21278, 34)\n", "Sample of gene expression data:\n", " GSM1575085 GSM1575086 GSM1575087 GSM1575088 GSM1575089 \\\n", "Gene \n", "A1BG 92.13980 87.1394 136.8800 169.79900 149.5720 \n", "A1BG-AS1 79.08870 29.9709 26.5951 97.24380 10.3971 \n", "A1CF 65.27392 146.8920 157.2644 117.82857 98.7029 \n", "A2M 5640.59000 10535.9921 5956.3960 4601.38610 10920.6929 \n", "A2M-AS1 95.51210 66.9938 72.5051 78.37100 102.9160 \n", "\n", " GSM1575090 GSM1575091 GSM1575092 GSM1575093 GSM1575094 ... \\\n", "Gene ... \n", "A1BG 137.5130 110.3330 180.97400 198.45200 292.8590 ... \n", "A1BG-AS1 86.5203 100.2560 14.18130 20.68470 98.5018 ... \n", "A1CF 93.7718 174.4951 122.40554 38.26969 186.8891 ... \n", "A2M 2494.5275 8309.0367 4087.66620 19431.86100 1693.5690 ... \n", "A2M-AS1 68.8274 51.4439 66.17640 63.74770 179.6830 ... \n", "\n", " GSM1575109 GSM1575110 GSM1575111 GSM1575112 GSM1575113 \\\n", "Gene \n", "A1BG 153.24700 321.1850 132.0920 202.59000 164.71600 \n", "A1BG-AS1 44.13270 4.8377 27.0553 143.29600 125.52800 \n", "A1CF 80.53890 84.5798 36.5748 88.72113 106.35991 \n", "A2M 5912.15264 3208.1601 14937.8089 5214.23420 2478.62510 \n", "A2M-AS1 161.38500 141.2550 74.8281 73.06360 158.03000 \n", "\n", " GSM1575114 GSM1575115 GSM1575116 GSM1575117 GSM1575118 \n", "Gene \n", "A1BG 188.7050 169.86000 144.15400 196.4090 189.3030 \n", "A1BG-AS1 17.7108 67.09200 18.29160 17.2501 14.6572 \n", "A1CF 163.9334 149.91933 283.41040 208.1441 136.5545 \n", "A2M 6350.7761 1336.01740 2184.26181 3854.5369 1826.5803 \n", "A2M-AS1 81.9210 51.26120 77.60570 75.1390 58.2430 \n", "\n", "[5 rows x 34 columns]\n", "Number of unique genes after mapping: 21278\n" ] } ], "source": [ "# 1. Identify which columns contain the gene identifiers and gene symbols\n", "# The column 'ID' in gene_annotation contains identifiers that match the gene expression data index\n", "# The column 'Gene Symbol' contains the gene symbols we need to map to\n", "prob_col = 'ID'\n", "gene_col = 'Gene Symbol'\n", "\n", "# 2. Extract the mapping dataframe using the get_gene_mapping function\n", "gene_mapping = get_gene_mapping(gene_annotation, prob_col, gene_col)\n", "print(f\"Gene mapping dataframe shape: {gene_mapping.shape}\")\n", "print(\"Sample of gene mapping:\")\n", "print(gene_mapping.head())\n", "\n", "# 3. Apply the gene mapping to convert probe-level measurements to gene expression data\n", "gene_data = apply_gene_mapping(gene_data, gene_mapping)\n", "print(f\"Gene expression data shape after mapping: {gene_data.shape}\")\n", "print(\"Sample of gene expression data:\")\n", "print(gene_data.head())\n", "\n", "# Check how many unique genes we have after mapping\n", "print(f\"Number of unique genes after mapping: {len(gene_data.index)}\")\n" ] }, { "cell_type": "markdown", "id": "ceb0ed36", "metadata": {}, "source": [ "### Step 7: Data Normalization and Linking" ] }, { "cell_type": "code", "execution_count": 8, "id": "a4949585", "metadata": { "execution": { "iopub.execute_input": "2025-03-25T08:21:59.169152Z", "iopub.status.busy": "2025-03-25T08:21:59.169049Z", "iopub.status.idle": "2025-03-25T08:21:59.594809Z", "shell.execute_reply": "2025-03-25T08:21:59.594444Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Gene data shape after normalization: (19845, 34)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Gene data saved to ../../output/preprocess/Chronic_obstructive_pulmonary_disease_(COPD)/gene_data/GSE64593.csv\n", "\n", "No COPD trait data available for this cohort.\n", "Dataset usability status: Not usable\n", "Dataset deemed not usable for COPD analysis due to missing trait data - linked data not created\n" ] } ], "source": [ "# 1. Normalize gene symbols in the gene expression data\n", "try:\n", " normalized_gene_data = normalize_gene_symbols_in_index(gene_data)\n", " print(f\"Gene data shape after normalization: {normalized_gene_data.shape}\")\n", " \n", " # Save normalized 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\"Gene data saved to {out_gene_data_file}\")\n", "except Exception as e:\n", " print(f\"Error during gene symbol normalization: {e}\")\n", " normalized_gene_data = gene_data\n", " print(\"Using original gene data (without normalization).\")\n", "\n", "# 2. Since we identified in step 2 that there's no COPD trait information available,\n", "# we cannot create clinical features or link the data\n", "print(\"\\nNo COPD trait data available for this cohort.\")\n", "\n", "# 3. Conduct initial validation since we can't do final validation without trait data\n", "is_usable = validate_and_save_cohort_info(\n", " is_final=False, # Use initial validation when trait data is unavailable\n", " cohort=cohort,\n", " info_path=json_path,\n", " is_gene_available=True,\n", " is_trait_available=False # We determined there's no COPD trait data in step 2\n", ")\n", "\n", "print(f\"Dataset usability status: {'Usable' if is_usable else 'Not usable'}\")\n", "print(\"Dataset deemed not usable for COPD analysis due to missing trait data - linked data not created\")" ] } ], "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 }