{ "cells": [ { "cell_type": "markdown", "id": "b4e01d14-77b9-49f5-a71e-ba1cee49ff09", "metadata": { "id": "b4e01d14-77b9-49f5-a71e-ba1cee49ff09" }, "source": [ "```\n", "---\n", "title: Enrichment analysis of proteins based on their GeneOntology annotations\n", "tags: GeneOntology, UniProt, enrichmentAnalysis, SPARQL\n", "lang: en\n", "version: 1.5\n", "date: 2026-04-01\n", "---\n", "```" ] }, { "cell_type": "code", "execution_count": 19, "id": "eYZ55aBKUrgg", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "eYZ55aBKUrgg", "outputId": "3aa54091-1d77-4e03-87f6-e7169a025b8b" }, "outputs": [], "source": [ "# if necessary extract the required files\n", "# !tar zxvf companionDirectories.tgz" ] }, { "cell_type": "code", "execution_count": 20, "id": "v3wh0oKWNz4V", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "v3wh0oKWNz4V", "outputId": "5217c2f5-397d-42c9-e42f-ee7486dfc8ea" }, "outputs": [], "source": [ "#!pip install graphviz" ] }, { "cell_type": "code", "execution_count": 21, "id": "5d895b04-463c-4169-b2f1-9a02dee2bb6b", "metadata": { "id": "5d895b04-463c-4169-b2f1-9a02dee2bb6b" }, "outputs": [], "source": [ "import graphviz\n", "import gzip\n", "#import importlib\n", "import IPython\n", "#import json\n", "import math\n", "#import matplotlib.pyplot as plt\n", "#import networkx as nx\n", "#import os\n", "import pandas as pd\n", "#import rdflib\n", "#import rdflib.namespace\n", "import scipy.stats as stats\n", "#import sparqldataframe\n", "#from SPARQLWrapper import SPARQLWrapper, JSON, POST\n", "#import sparqldataframe\n", "#import sys" ] }, { "cell_type": "code", "execution_count": 22, "id": "54b5fdfa-e0bc-4914-b10f-e2398a15423c", "metadata": { "id": "54b5fdfa-e0bc-4914-b10f-e2398a15423c" }, "outputs": [], "source": [ "taxon = {\"id\":\"9606\", \"name\":\"human\"}" ] }, { "cell_type": "markdown", "id": "41451973-4d77-4e93-a2d6-402665dff035", "metadata": { "id": "41451973-4d77-4e93-a2d6-402665dff035" }, "source": [ "# 1. Setup your environment" ] }, { "cell_type": "code", "execution_count": 23, "id": "354c836f-9004-494a-9397-f85f91975174", "metadata": { "id": "354c836f-9004-494a-9397-f85f91975174" }, "outputs": [], "source": [ "#specify no max value for the column width\n", "pd.set_option('display.max_colwidth', None)" ] }, { "cell_type": "markdown", "id": "9b472bba-e425-4d58-87aa-cac80bdbc1b0", "metadata": { "id": "9b472bba-e425-4d58-87aa-cac80bdbc1b0" }, "source": [ "## 1.1 Utility functions" ] }, { "cell_type": "code", "execution_count": 24, "id": "d1c1f1df-85f3-4f1c-adf8-1737a27f7bda", "metadata": { "id": "d1c1f1df-85f3-4f1c-adf8-1737a27f7bda" }, "outputs": [], "source": [ "def getColor(pvalue, lowestPvalue):\n", " val = int((1. - (math.log(pvalue, 10)/math.log(lowestPvalue, 10))) * 255)\n", " #return '0xff{:02x}{:02x}'.format(val, val)\n", " return '#ff{:02x}{:02x}'.format(val, val)" ] }, { "cell_type": "code", "execution_count": 25, "id": "5afca51e-a095-4a8c-b608-48c08e2e710b", "metadata": { "id": "5afca51e-a095-4a8c-b608-48c08e2e710b" }, "outputs": [], "source": [ "def addAnnotationAncestors(goIdent, dfAnnotationsColors, dfAnnotationsLabel, dfAnnotationsParents, dfAnnotationsAncestors, graph=None):\n", " if graph is None:\n", " graph = Digraph(graph_attr={'rankdir': 'BT'}, strict=True)\n", " for ancestorID in dfAnnotationsAncestors[dfAnnotationsAncestors['goID'] == goIdent]['goAncestorID'].tolist() + [goIdent]:\n", " nodeColor = \"white\"\n", " borderColor = \"black\"\n", " if ancestorID in dfAnnotationsColors.index:\n", " nodeColor = dfAnnotationsColors[\"rgb\"][ancestorID]\n", " borderColor = \"red\"\n", " ancestorIDnumber = ancestorID.replace(\"http://purl.obolibrary.org/obo/GO_\", \"\")\n", " graph.node(\"go\"+ancestorIDnumber, label=\"go:{}\\n{}\".format(ancestorIDnumber, dfAnnotationsLabel.loc[ancestorID, 'goLabel']), shape=\"box\", style=\"filled\", fillcolor=nodeColor, color=borderColor)\n", "\n", " for ancestorParentID in dfAnnotationsParents[dfAnnotationsParents['goID'] == ancestorID]['goParentID'].tolist():\n", " nodeColor = \"white\"\n", " borderColor = \"black\"\n", " if ancestorParentID in dfAnnotationsColors.index:\n", " nodeColor = dfAnnotationsColors[\"rgb\"][ancestorParentID]\n", " borderColor = \"red\"\n", " ancestorParentIDnumber = ancestorParentID.replace(\"http://purl.obolibrary.org/obo/GO_\", \"\")\n", " graph.node(\"go\"+ancestorParentIDnumber, label=\"go:{}\\n{}\".format(ancestorParentIDnumber, dfAnnotationsLabel.loc[ancestorParentID, 'goLabel']), shape=\"box\", style=\"filled\", fillcolor=nodeColor, color=borderColor)\n", " graph.edge(\"go\"+ancestorIDnumber, \"go\"+ancestorParentIDnumber, arrowhead=\"onormal\")\n", " return graph" ] }, { "cell_type": "markdown", "id": "11f0c9bb-ca0f-4b9b-96c9-a914e31d4413", "metadata": { "id": "11f0c9bb-ca0f-4b9b-96c9-a914e31d4413" }, "source": [ "## 1.2 Load precomputed data" ] }, { "cell_type": "markdown", "id": "4f969855-dfc1-4a44-bc74-e4a561b5e931", "metadata": { "id": "4f969855-dfc1-4a44-bc74-e4a561b5e931" }, "source": [ "
\n", "Tip: use notebook enrichmentAnalysisGO-preprocess.ipynb to generate them\n", "
" ] }, { "cell_type": "code", "execution_count": 26, "id": "4fe7defa-6e02-49f6-8df7-5b069f39462d", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 235 }, "id": "4fe7defa-6e02-49f6-8df7-5b069f39462d", "outputId": "a0406480-0777-4ba9-e623-5e76f5ec0c76" }, "outputs": [ { "data": { "text/html": [ "
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goLabel
goID
http://purl.obolibrary.org/obo/GO_0070549siRNA-mediated gene silencing by inhibition of translation
http://purl.obolibrary.org/obo/GO_0070542response to fatty acid
http://purl.obolibrary.org/obo/GO_0070541response to platinum ion
http://purl.obolibrary.org/obo/GO_0070543response to linoleic acid
http://purl.obolibrary.org/obo/GO_0070545PeBoW complex
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" ], "text/plain": [ " goLabel\n", "goID \n", "http://purl.obolibrary.org/obo/GO_0070549 siRNA-mediated gene silencing by inhibition of translation\n", "http://purl.obolibrary.org/obo/GO_0070542 response to fatty acid\n", "http://purl.obolibrary.org/obo/GO_0070541 response to platinum ion\n", "http://purl.obolibrary.org/obo/GO_0070543 response to linoleic acid\n", "http://purl.obolibrary.org/obo/GO_0070545 PeBoW complex" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dfGOlabel = pd.read_csv(\"results/GeneOntology_label.tsv.gz\", compression='gzip', delimiter='\\t', names=[\"goID\", \"goLabel\"], index_col=\"goID\")\n", "dfGOlabel.drop_duplicates(subset=None, keep='first', inplace=True)\n", "dfGOlabel.head()" ] }, { "cell_type": "code", "execution_count": 27, "id": "e8e8ef49-97a9-452c-aca4-6970586e62fc", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "id": "e8e8ef49-97a9-452c-aca4-6970586e62fc", "outputId": "a4018a0e-94c2-4fb5-8637-2a9cffc8fa59" }, "outputs": [ { "data": { "text/html": [ "
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goIDgoParentID
0http://purl.obolibrary.org/obo/GO_0040007http://purl.obolibrary.org/obo/GO_0008150
1http://purl.obolibrary.org/obo/GO_0080190http://purl.obolibrary.org/obo/GO_0040007
2http://purl.obolibrary.org/obo/GO_0080191http://purl.obolibrary.org/obo/GO_0080190
3http://purl.obolibrary.org/obo/GO_0080117http://purl.obolibrary.org/obo/GO_0080190
4http://purl.obolibrary.org/obo/GO_0080193http://purl.obolibrary.org/obo/GO_0080190
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" ], "text/plain": [ " goID \\\n", "0 http://purl.obolibrary.org/obo/GO_0040007 \n", "1 http://purl.obolibrary.org/obo/GO_0080190 \n", "2 http://purl.obolibrary.org/obo/GO_0080191 \n", "3 http://purl.obolibrary.org/obo/GO_0080117 \n", "4 http://purl.obolibrary.org/obo/GO_0080193 \n", "\n", " goParentID \n", "0 http://purl.obolibrary.org/obo/GO_0008150 \n", "1 http://purl.obolibrary.org/obo/GO_0040007 \n", "2 http://purl.obolibrary.org/obo/GO_0080190 \n", "3 http://purl.obolibrary.org/obo/GO_0080190 \n", "4 http://purl.obolibrary.org/obo/GO_0080190 " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dfGOparents = pd.read_csv(\"results/GeneOntology_parents.tsv.gz\", compression='gzip', delimiter='\\t', names=[\"goID\", \"goParentID\"])\n", "dfGOparents.drop_duplicates(subset=None, keep='first', inplace=True)\n", "dfGOparents.head()" ] }, { "cell_type": "code", "execution_count": 28, "id": "87df30e2-cd5b-4a16-96c7-c0f68f50bd29", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "id": "87df30e2-cd5b-4a16-96c7-c0f68f50bd29", "outputId": "25bc1414-2783-427a-fca8-4c811e8d9dd0" }, "outputs": [ { "data": { "text/html": [ "
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goIDgoAncestorID
0http://purl.obolibrary.org/obo/GO_0040007http://purl.obolibrary.org/obo/GO_0008150
1http://purl.obolibrary.org/obo/GO_0080190http://purl.obolibrary.org/obo/GO_0040007
2http://purl.obolibrary.org/obo/GO_0080190http://purl.obolibrary.org/obo/GO_0008150
3http://purl.obolibrary.org/obo/GO_0080191http://purl.obolibrary.org/obo/GO_0080190
4http://purl.obolibrary.org/obo/GO_0080191http://purl.obolibrary.org/obo/GO_0040007
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" ], "text/plain": [ " goID \\\n", "0 http://purl.obolibrary.org/obo/GO_0040007 \n", "1 http://purl.obolibrary.org/obo/GO_0080190 \n", "2 http://purl.obolibrary.org/obo/GO_0080190 \n", "3 http://purl.obolibrary.org/obo/GO_0080191 \n", "4 http://purl.obolibrary.org/obo/GO_0080191 \n", "\n", " goAncestorID \n", "0 http://purl.obolibrary.org/obo/GO_0008150 \n", "1 http://purl.obolibrary.org/obo/GO_0040007 \n", "2 http://purl.obolibrary.org/obo/GO_0008150 \n", "3 http://purl.obolibrary.org/obo/GO_0080190 \n", "4 http://purl.obolibrary.org/obo/GO_0040007 " ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dfGOancestors = pd.read_csv(\"results/GeneOntology_ancestors.tsv.gz\", compression='gzip', delimiter='\\t', names=[\"goID\", \"goAncestorID\"])\n", "dfGOancestors.drop_duplicates(subset=None, keep='first', inplace=True)\n", "dfGOancestors.head()" ] }, { "cell_type": "code", "execution_count": 29, "id": "ecbf4b22-8a52-4bff-bedc-ef474fdcadb3", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "id": "ecbf4b22-8a52-4bff-bedc-ef474fdcadb3", "outputId": "11a8a4fd-5ebe-4901-8f35-f9f160bba9a5" }, "outputs": [ { "data": { "text/html": [ "
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uniprotIDgoID
0http://purl.uniprot.org/uniprot/Q12774http://purl.obolibrary.org/obo/GO_0035556
1http://purl.uniprot.org/uniprot/Q12774http://purl.obolibrary.org/obo/GO_0007165
2http://purl.uniprot.org/uniprot/Q12774http://purl.obolibrary.org/obo/GO_0009987
3http://purl.uniprot.org/uniprot/Q12774http://purl.obolibrary.org/obo/GO_0008150
4http://purl.uniprot.org/uniprot/Q12774http://purl.obolibrary.org/obo/GO_0050794
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" ], "text/plain": [ " uniprotID \\\n", "0 http://purl.uniprot.org/uniprot/Q12774 \n", "1 http://purl.uniprot.org/uniprot/Q12774 \n", "2 http://purl.uniprot.org/uniprot/Q12774 \n", "3 http://purl.uniprot.org/uniprot/Q12774 \n", "4 http://purl.uniprot.org/uniprot/Q12774 \n", "\n", " goID \n", "0 http://purl.obolibrary.org/obo/GO_0035556 \n", "1 http://purl.obolibrary.org/obo/GO_0007165 \n", "2 http://purl.obolibrary.org/obo/GO_0009987 \n", "3 http://purl.obolibrary.org/obo/GO_0008150 \n", "4 http://purl.obolibrary.org/obo/GO_0050794 " ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dfProteinGO = pd.read_csv(\"results/\" + taxon[\"name\"] + \"_Proteins_annotations.tsv.gz\", compression='gzip', delimiter='\\t', names=[\"uniprotID\", \"goID\"])\n", "dfProteinGO.drop_duplicates(subset=None, keep='first', inplace=True)\n", "dfProteinGO.head()" ] }, { "cell_type": "code", "execution_count": 30, "id": "36e364b7-f118-4388-a983-62981dc248e8", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "36e364b7-f118-4388-a983-62981dc248e8", "outputId": "985cbdb6-b09c-4652-91a1-a6374bb424ba" }, "outputs": [ { "data": { "text/plain": [ "19700" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nbUniprotReference = len(dfProteinGO[\"uniprotID\"].unique())\n", "nbUniprotReference" ] }, { "cell_type": "code", "execution_count": 31, "id": "69a26487-0f18-400b-bc99-9d5f12e91684", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 450 }, "id": "69a26487-0f18-400b-bc99-9d5f12e91684", "outputId": "f6f2adb2-ae81-48bd-f350-afa424e548ee" }, "outputs": [ { "data": { "text/html": [ "
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nbUniprotReferencegoLabel
goID
http://purl.obolibrary.org/obo/GO_000557519019cellular_component
http://purl.obolibrary.org/obo/GO_011016518893cellular anatomical structure
http://purl.obolibrary.org/obo/GO_000367418290molecular_function
http://purl.obolibrary.org/obo/GO_000815017801biological_process
http://purl.obolibrary.org/obo/GO_000548816553binding
.........
http://purl.obolibrary.org/obo/GO_00352121cell competition in a multicellular organism
http://purl.obolibrary.org/obo/GO_01203221lipid modification by small protein conjugation
http://purl.obolibrary.org/obo/GO_01203231lipid ubiquitination
http://purl.obolibrary.org/obo/GO_00051751CD27 receptor binding
http://purl.obolibrary.org/obo/GO_00043251ferrochelatase activity
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20658 rows × 2 columns

\n", "
" ], "text/plain": [ " nbUniprotReference \\\n", "goID \n", "http://purl.obolibrary.org/obo/GO_0005575 19019 \n", "http://purl.obolibrary.org/obo/GO_0110165 18893 \n", "http://purl.obolibrary.org/obo/GO_0003674 18290 \n", "http://purl.obolibrary.org/obo/GO_0008150 17801 \n", "http://purl.obolibrary.org/obo/GO_0005488 16553 \n", "... ... \n", "http://purl.obolibrary.org/obo/GO_0035212 1 \n", "http://purl.obolibrary.org/obo/GO_0120322 1 \n", "http://purl.obolibrary.org/obo/GO_0120323 1 \n", "http://purl.obolibrary.org/obo/GO_0005175 1 \n", "http://purl.obolibrary.org/obo/GO_0004325 1 \n", "\n", " goLabel \n", "goID \n", "http://purl.obolibrary.org/obo/GO_0005575 cellular_component \n", "http://purl.obolibrary.org/obo/GO_0110165 cellular anatomical structure \n", "http://purl.obolibrary.org/obo/GO_0003674 molecular_function \n", "http://purl.obolibrary.org/obo/GO_0008150 biological_process \n", "http://purl.obolibrary.org/obo/GO_0005488 binding \n", "... ... \n", "http://purl.obolibrary.org/obo/GO_0035212 cell competition in a multicellular organism \n", "http://purl.obolibrary.org/obo/GO_0120322 lipid modification by small protein conjugation \n", "http://purl.obolibrary.org/obo/GO_0120323 lipid ubiquitination \n", "http://purl.obolibrary.org/obo/GO_0005175 CD27 receptor binding \n", "http://purl.obolibrary.org/obo/GO_0004325 ferrochelatase activity \n", "\n", "[20658 rows x 2 columns]" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "occurrencesGOreference = dfProteinGO[\"goID\"].value_counts()\n", "occurrencesGOreference.rename(\"nbUniprotReference\", inplace=True)\n", "occurrencesGOreference = occurrencesGOreference.to_frame()\n", "occurrencesGOreference = occurrencesGOreference.merge(dfGOlabel, left_index=True, right_index=True)\n", "\n", "occurrencesGOreference" ] }, { "cell_type": "markdown", "id": "91902ef5-2185-4313-b0b9-fadcd149e272", "metadata": { "id": "91902ef5-2185-4313-b0b9-fadcd149e272" }, "source": [ "# 2. Enrichment analysis" ] }, { "cell_type": "code", "execution_count": 32, "id": "a180c9b7-648e-49f7-956b-0de55c1c7ef3", "metadata": { "id": "a180c9b7-648e-49f7-956b-0de55c1c7ef3" }, "outputs": [], "source": [ "#adjPvalueMethod = \"None\"\n", "adjPvalueMethod = \"Bonferroni\"\n", "#adjPvalueMethod = \"Benjamini-Hochberg\"\n", "\n", "\n", "adjPvalueThreshold = 0.05\n", "\n", "moduleName = \"geneSet_1\"\n", "#moduleName = \"geneSet_random\"\n", "\n", "#moduleName = \"module-mRNA-black\"\n", "#moduleName = \"module-mRNA-blue\"\n", "#moduleName = \"module-mRNA-brown\"\n", "#moduleName = \"module-mRNA-red\"\n", "#moduleName = \"module-mRNA-yellow\"\n", "##moduleName = \"module-mRNA-turquoise\"\n", "###moduleName = \"module-mRNA-green\"\n", "###moduleName = \"module-mRNA-grey\"\n", "###moduleName = \"module-mRNA-pink\"\n", "\n", "useDefaultBackgound = True\n", "#useDefaultBackgound = False\n", "\n", "if not useDefaultBackgound:\n", " #backgroundSetName = \"moduleProtein-reference\"\n", " backgroundSetName = \"module-mRNA-reference\"\n", "\n", "multipleTestsPValue = \"adjPvalue\" if adjPvalueMethod == \"Benjamini-Hochberg\" else \"Evalue\"" ] }, { "cell_type": "code", "execution_count": 33, "id": "373fa01c-a0e1-4717-ae89-ae77441b21c5", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 526 }, "id": "373fa01c-a0e1-4717-ae89-ae77441b21c5", "outputId": "c726f305-c3f7-4257-8ac5-bb6709b4806b" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "File: geneSet_1\n", "nbUniprotInSet: 11\n", "nbGOInSet: 259\n", "nbUniprotReference: 19700\n", "Multiple tests correction method: Bonferroni\n", "Nb significantly enriched annotations: 41\n", "Rendering\n", "Top-10 enriched GO terms\n" ] }, { "data": { "text/html": [ "
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nbUniprotModulenbUniprotReferencegoLabelpValueEvalue
goID
http://purl.obolibrary.org/obo/GO_00067841010heme A biosynthetic process4.544495e-361.177024e-33
http://purl.obolibrary.org/obo/GO_00067831129heme biosynthetic process7.985131e-332.068149e-30
http://purl.obolibrary.org/obo/GO_00067791131porphyrin-containing compound biosynthetic process1.954256e-325.061522e-30
http://purl.obolibrary.org/obo/GO_00330141131tetrapyrrole biosynthetic process1.954256e-325.061522e-30
http://purl.obolibrary.org/obo/GO_004650199protoporphyrinogen IX metabolic process4.474283e-321.158839e-29
http://purl.obolibrary.org/obo/GO_0006785910heme B biosynthetic process4.473874e-311.158733e-28
http://purl.obolibrary.org/obo/GO_00461481144pigment biosynthetic process1.770100e-304.584560e-28
http://purl.obolibrary.org/obo/GO_00421681147heme metabolic process4.019913e-301.041157e-27
http://purl.obolibrary.org/obo/GO_00067781150porphyrin-containing compound metabolic process8.621325e-302.232923e-27
http://purl.obolibrary.org/obo/GO_00330131159tetrapyrrole metabolic process6.459502e-291.673011e-26
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" ], "text/plain": [ " nbUniprotModule \\\n", "goID \n", "http://purl.obolibrary.org/obo/GO_0006784 10 \n", "http://purl.obolibrary.org/obo/GO_0006783 11 \n", "http://purl.obolibrary.org/obo/GO_0006779 11 \n", "http://purl.obolibrary.org/obo/GO_0033014 11 \n", "http://purl.obolibrary.org/obo/GO_0046501 9 \n", "http://purl.obolibrary.org/obo/GO_0006785 9 \n", "http://purl.obolibrary.org/obo/GO_0046148 11 \n", "http://purl.obolibrary.org/obo/GO_0042168 11 \n", "http://purl.obolibrary.org/obo/GO_0006778 11 \n", "http://purl.obolibrary.org/obo/GO_0033013 11 \n", "\n", " nbUniprotReference \\\n", "goID \n", "http://purl.obolibrary.org/obo/GO_0006784 10 \n", "http://purl.obolibrary.org/obo/GO_0006783 29 \n", "http://purl.obolibrary.org/obo/GO_0006779 31 \n", "http://purl.obolibrary.org/obo/GO_0033014 31 \n", "http://purl.obolibrary.org/obo/GO_0046501 9 \n", "http://purl.obolibrary.org/obo/GO_0006785 10 \n", "http://purl.obolibrary.org/obo/GO_0046148 44 \n", "http://purl.obolibrary.org/obo/GO_0042168 47 \n", "http://purl.obolibrary.org/obo/GO_0006778 50 \n", "http://purl.obolibrary.org/obo/GO_0033013 59 \n", "\n", " goLabel \\\n", "goID \n", "http://purl.obolibrary.org/obo/GO_0006784 heme A biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0006783 heme biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0006779 porphyrin-containing compound biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0033014 tetrapyrrole biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0046501 protoporphyrinogen IX metabolic process \n", "http://purl.obolibrary.org/obo/GO_0006785 heme B biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0046148 pigment biosynthetic process \n", "http://purl.obolibrary.org/obo/GO_0042168 heme metabolic process \n", "http://purl.obolibrary.org/obo/GO_0006778 porphyrin-containing compound metabolic process \n", "http://purl.obolibrary.org/obo/GO_0033013 tetrapyrrole metabolic process \n", "\n", " pValue Evalue \n", "goID \n", "http://purl.obolibrary.org/obo/GO_0006784 4.544495e-36 1.177024e-33 \n", "http://purl.obolibrary.org/obo/GO_0006783 7.985131e-33 2.068149e-30 \n", "http://purl.obolibrary.org/obo/GO_0006779 1.954256e-32 5.061522e-30 \n", "http://purl.obolibrary.org/obo/GO_0033014 1.954256e-32 5.061522e-30 \n", "http://purl.obolibrary.org/obo/GO_0046501 4.474283e-32 1.158839e-29 \n", "http://purl.obolibrary.org/obo/GO_0006785 4.473874e-31 1.158733e-28 \n", "http://purl.obolibrary.org/obo/GO_0046148 1.770100e-30 4.584560e-28 \n", "http://purl.obolibrary.org/obo/GO_0042168 4.019913e-30 1.041157e-27 \n", "http://purl.obolibrary.org/obo/GO_0006778 8.621325e-30 2.232923e-27 \n", "http://purl.obolibrary.org/obo/GO_0033013 6.459502e-29 1.673011e-26 " ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 1. load set of proteins of interest\n", "dfSet = pd.read_csv(\"data/{}.txt\".format(moduleName), delimiter='\\t', names=[\"uniprotCURIE\"])\n", "dfSet[\"uniprotID\"] = dfSet[\"uniprotCURIE\"].str.replace(\"uniprot:\", \"http://purl.uniprot.org/uniprot/\")\n", "dfSet = dfSet[\"uniprotID\"].to_frame()\n", "dfSet = dfSet.sort_values(by=['uniprotID'], ascending=True).drop_duplicates(subset='uniprotID', ignore_index=True)\n", "dfSet.set_index(\"uniprotID\", inplace=True)\n", "nbUniprotInSet = len(dfSet)\n", "print(\"File: {}\".format(moduleName))\n", "print(\"nbUniprotInSet: {}\".format(nbUniprotInSet))\n", "\n", "\n", "# 2. count GO annotation frequencies among the set of proteins of interest\n", "dfProteinGOSet = dfProteinGO.merge(dfSet, left_on=\"uniprotID\", right_on=\"uniprotID\")\n", "occurrencesGOSet = dfProteinGOSet[\"goID\"].value_counts()\n", "occurrencesGOSet.rename(\"nbUniprotModule\", inplace=True)\n", "nbGOInSet = len(dfProteinGOSet[\"goID\"].unique())\n", "print(\"nbGOInSet: {}\".format(nbGOInSet))\n", "\n", "imageFileName = None\n", "\n", "# 3. count GO annotation frequencies among the set of background proteins\n", "if useDefaultBackgound:\n", " nbUniprotReference = len(dfProteinGO[\"uniprotID\"].unique())\n", " occurrencesGOreference = dfProteinGO[\"goID\"].value_counts()\n", " occurrencesGOreference.rename(\"nbUniprotReference\", inplace=True)\n", " occurrencesGOreference = occurrencesGOreference.to_frame()\n", " occurrencesGOreference = occurrencesGOreference.merge(dfGOlabel, left_index=True, right_index=True)\n", "else:\n", " dfReferenceCustom = pd.read_csv(\"data/{}.txt\".format(backgroundSetName), delimiter='\\t', names=[\"uniprotCURIE\"])\n", " dfReferenceCustom[\"uniprotID\"] = dfReferenceCustom[\"uniprotCURIE\"].str.replace(\"uniprot:\", \"http://purl.uniprot.org/uniprot/\")\n", " dfReferenceCustom = dfReferenceCustom[\"uniprotID\"].to_frame()\n", " dfReferenceCustom = dfReferenceCustom.sort_values(by=['uniprotID'], ascending=True).drop_duplicates(subset='uniprotID', ignore_index=True)\n", " dfReferenceCustom.set_index(\"uniprotID\", inplace=True)\n", "\n", " dfProteinGOreferenceCustom = dfProteinGO.merge(dfReferenceCustom, left_on=\"uniprotID\", right_on=\"uniprotID\")\n", " nbUniprotReference = len(dfProteinGOreferenceCustom['uniprotID'].unique())\n", "\n", " occurrencesGOreference = dfProteinGOreferenceCustom[\"goID\"].value_counts()\n", " occurrencesGOreference.rename(\"nbUniprotReference\", inplace=True)\n", " occurrencesGOreference = occurrencesGOreference.to_frame()\n", " occurrencesGOreference = occurrencesGOreference.merge(dfGOlabel, left_index=True, right_index=True)\n", " occurrencesGOreference.head()\n", "print(\"nbUniprotReference: {}\".format(nbUniprotReference))\n", "\n", "# 4. compute enrichment\n", "occurrencesGO = pd.merge(occurrencesGOSet, occurrencesGOreference, right_index = True, left_index = True)\n", "occurrencesGO[\"pValue\"] = stats.hypergeom.sf(occurrencesGO['nbUniprotModule']-1, nbUniprotReference, occurrencesGO['nbUniprotReference'], nbUniprotInSet)\n", "if adjPvalueMethod == \"Benjamini-Hochberg\":\n", " occurrencesGO[\"adjPvalue\"] = stats.false_discovery_control(occurrencesGO[\"pValue\"]) # Benjamini-Hochberg\n", "elif adjPvalueMethod == \"Bonferroni\":\n", " occurrencesGO[multipleTestsPValue] = occurrencesGO[\"pValue\"] * nbGOInSet # Bonferroni\n", "else:\n", " occurrencesGO[multipleTestsPValue] = occurrencesGO[\"pValue\"]\n", "\n", "print(\"Multiple tests correction method: {}\".format(adjPvalueMethod))\n", "annotationsWithColors = occurrencesGO[occurrencesGO[multipleTestsPValue] < adjPvalueThreshold].sort_values(by=multipleTestsPValue)\n", "if len(annotationsWithColors) == 0:\n", " print(\"No significantly enriched annotation\")\n", "else:\n", " print(\"Nb significantly enriched annotations: {}\".format(len(annotationsWithColors)))\n", " #print(annotationsWithColors)\n", " minPval = annotationsWithColors[multipleTestsPValue].min()\n", " maxPval = annotationsWithColors[multipleTestsPValue].max()\n", " annotationsWithColors[\"rgb\"] = annotationsWithColors[multipleTestsPValue].map(lambda x: getColor(x, minPval))\n", "\n", " filteredGraph = graphviz.graphs.Digraph(graph_attr={'rankdir': 'BT'}, strict=True)\n", " for currentGO in annotationsWithColors.index:\n", " addAnnotationAncestors(currentGO, annotationsWithColors, dfGOlabel, dfGOparents, dfGOancestors, filteredGraph)\n", " print(\"Rendering\")\n", " imageFileName = \"results/{}-reduced_background-{}_multipleTests-{}\".format(moduleName, \"default\" if useDefaultBackgound else \"custom\", adjPvalueMethod)\n", " filteredGraph.render(imageFileName, cleanup=True, format='svg')\n", "\n", "# for examining the GO terms enrichment\n", "print(\"Top-10 enriched GO terms\")\n", "occurrencesGO.sort_values(by=multipleTestsPValue).head(10)\n", "#\n", "# for examining a specific GO term\n", "#occurrencesGO.loc[\"http://purl.obolibrary.org/obo/GO_0008150\"]" ] }, { "cell_type": "code", "execution_count": 34, "id": "c6b8ca6d-20f3-4472-bae6-eaf867bf4d0b", "metadata": { "colab": { 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"cellular_component\n", "\n", "\n", "\n", "go0110165->go0005575\n", "\n", "\n", "\n", "\n", "\n", "go0031966\n", "\n", "go:0031966\n", "mitochondrial membrane\n", "\n", "\n", "\n", "go0031966->go0031090\n", "\n", "\n", "\n", "\n", "\n", "go0005743\n", "\n", "go:0005743\n", "mitochondrial inner membrane\n", "\n", "\n", "\n", "go0005743->go0019866\n", "\n", "\n", "\n", "\n", "\n", "go0005743->go0031966\n", "\n", "\n", "\n", "\n", "\n", "go0043231\n", "\n", "go:0043231\n", "intracellular membrane-bounded organelle\n", "\n", "\n", "\n", "go0043227\n", "\n", "go:0043227\n", "membrane-bounded organelle\n", "\n", "\n", "\n", "go0043231->go0043227\n", "\n", "\n", "\n", "\n", "\n", "go0043229\n", "\n", "go:0043229\n", "intracellular organelle\n", "\n", "\n", "\n", "go0043231->go0043229\n", "\n", "\n", "\n", "\n", "\n", "go0043226\n", "\n", "go:0043226\n", "organelle\n", "\n", "\n", "\n", "go0043227->go0043226\n", "\n", "\n", "\n", "\n", "\n", "go0043229->go0043226\n", "\n", "\n", "\n", "\n", "\n", "go0043226->go0110165\n", "\n", "\n", "\n", "\n", "\n", "go0005739\n", "\n", "go:0005739\n", "mitochondrion\n", "\n", "\n", "\n", "go0005739->go0043231\n", "\n", "\n", "\n", "\n", "\n", "go0016749\n", "\n", "go:0016749\n", "N-succinyltransferase activity\n", "\n", "\n", "\n", "go0016748\n", "\n", "go:0016748\n", "succinyltransferase activity\n", "\n", "\n", "\n", "go0016749->go0016748\n", "\n", "\n", "\n", "\n", "\n", "go0016410\n", "\n", "go:0016410\n", "N-acyltransferase activity\n", "\n", "\n", "\n", "go0016749->go0016410\n", "\n", "\n", "\n", "\n", "\n", "go0016747\n", "\n", "go:0016747\n", "acyltransferase activity, transferring groups other than amino-acyl groups\n", "\n", "\n", "\n", "go0016748->go0016747\n", "\n", "\n", "\n", "\n", "\n", "go0016410->go0016747\n", "\n", "\n", "\n", "\n", "\n", "go0016746\n", "\n", "go:0016746\n", "acyltransferase activity\n", "\n", "\n", "\n", "go0016747->go0016746\n", "\n", "\n", "\n", "\n", "\n", "go0016740\n", "\n", "go:0016740\n", "transferase activity\n", "\n", "\n", "\n", "go0016746->go0016740\n", "\n", "\n", "\n", "\n", "\n", "go0003824\n", "\n", "go:0003824\n", "catalytic activity\n", "\n", "\n", "\n", "go0016740->go0003824\n", "\n", "\n", "\n", "\n", "\n", "go0003674\n", "\n", "go:0003674\n", "molecular_function\n", "\n", "\n", "\n", "go0003824->go0003674\n", "\n", "\n", "\n", "\n", "\n", "go0003870\n", "\n", "go:0003870\n", "5-aminolevulinate synthase activity\n", "\n", "\n", "\n", "go0003870->go0016749\n", "\n", "\n", "\n", "\n", "\n", "go0046685\n", "\n", "go:0046685\n", "response to arsenic-containing substance\n", "\n", "\n", "\n", "go0046685->go0042221\n", "\n", "\n", "\n", "\n", "\n", "go0020027\n", "\n", "go:0020027\n", "hemoglobin metabolic process\n", "\n", "\n", "\n", "go0019538\n", "\n", "go:0019538\n", "protein metabolic process\n", "\n", "\n", "\n", "go0020027->go0019538\n", "\n", "\n", "\n", "\n", "\n", "go0044238\n", "\n", "go:0044238\n", "primary metabolic process\n", "\n", "\n", "\n", "go0019538->go0044238\n", "\n", "\n", "\n", "\n", "\n", "go0043170\n", "\n", "go:0043170\n", "macromolecule metabolic process\n", "\n", "\n", "\n", "go0019538->go0043170\n", "\n", "\n", "\n", "\n", "\n", "go0044238->go0008152\n", "\n", "\n", "\n", "\n", "\n", "go0043170->go0008152\n", "\n", "\n", "\n", "\n", "\n", "go0009059\n", "\n", "go:0009059\n", "macromolecule biosynthetic process\n", "\n", "\n", "\n", "go0009059->go0009058\n", "\n", "\n", "\n", "\n", "\n", "go0009059->go0043170\n", "\n", "\n", "\n", "\n", "\n", "go0042541\n", "\n", "go:0042541\n", "hemoglobin biosynthetic process\n", "\n", "\n", "\n", "go0042541->go0020027\n", "\n", "\n", "\n", "\n", "\n", "go0042541->go0009059\n", "\n", "\n", "\n", "\n", "\n", "go0031974\n", "\n", "go:0031974\n", "membrane-enclosed lumen\n", "\n", "\n", "\n", "go0031974->go0110165\n", "\n", "\n", "\n", "\n", "\n", "go0043233\n", "\n", "go:0043233\n", "organelle lumen\n", "\n", "\n", "\n", "go0043233->go0031974\n", "\n", "\n", "\n", "\n", "\n", "go0070013\n", "\n", "go:0070013\n", "intracellular organelle lumen\n", "\n", "\n", "\n", "go0070013->go0043233\n", "\n", "\n", "\n", "\n", "\n", "go0006950\n", "\n", "go:0006950\n", "response to stress\n", "\n", "\n", "\n", "go0006950->go0050896\n", "\n", "\n", "\n", "\n", "\n", "go0009636\n", "\n", "go:0009636\n", "response to toxic substance\n", "\n", "\n", "\n", "go0009636->go0042221\n", "\n", "\n", "\n", "\n", "\n", "go0009635\n", "\n", "go:0009635\n", "response to herbicide\n", "\n", "\n", "\n", "go0009635->go0006950\n", "\n", "\n", "\n", "\n", "\n", "go0009635->go0009636\n", "\n", "\n", "\n", "\n", "\n", "go0051597\n", "\n", "go:0051597\n", "response to methylmercury\n", "\n", "\n", "\n", "go0051597->go0042221\n", "\n", "\n", "\n", "\n", "\n", "go0016829\n", "\n", "go:0016829\n", "lyase activity\n", "\n", "\n", "\n", "go0016829->go0003824\n", "\n", "\n", "\n", "\n", "\n", "go0016491\n", "\n", "go:0016491\n", "oxidoreductase activity\n", "\n", "\n", "\n", "go0016491->go0003824\n", "\n", "\n", "\n", "\n", "\n", "go0016627\n", "\n", "go:0016627\n", "oxidoreductase activity, acting on the CH-CH group of donors\n", "\n", "\n", "\n", "go0016627->go0016491\n", "\n", "\n", "\n", "\n", "\n", "go0016634\n", "\n", "go:0016634\n", "oxidoreductase activity, acting on the CH-CH group of donors, oxygen as acceptor\n", "\n", "\n", "\n", "go0016634->go0016627\n", "\n", "\n", "\n", "\n", "\n", "go0032025\n", "\n", "go:0032025\n", "response to cobalt ion\n", "\n", "\n", "\n", "go0032025->go0010038\n", "\n", "\n", "\n", "\n", "\n", "go0010288\n", "\n", "go:0010288\n", "response to lead ion\n", "\n", "\n", "\n", "go0010288->go0010038\n", "\n", "\n", "\n", "\n", "\n", "go0036094\n", "\n", "go:0036094\n", "small molecule binding\n", "\n", "\n", "\n", "go0005488\n", "\n", "go:0005488\n", "binding\n", "\n", "\n", "\n", "go0036094->go0005488\n", "\n", "\n", "\n", "\n", "\n", "go0005488->go0003674\n", "\n", "\n", "\n", "\n", "\n", "go0019842\n", "\n", "go:0019842\n", "vitamin binding\n", "\n", "\n", "\n", "go0019842->go0036094\n", "\n", "\n", "\n", "\n", "\n", "go0005759\n", "\n", "go:0005759\n", "mitochondrial matrix\n", "\n", "\n", "\n", "go0005759->go0070013\n", "\n", "\n", "\n", "\n", "\n", "go0010039\n", "\n", "go:0010039\n", "response to iron ion\n", "\n", "\n", "\n", "go0010039->go0010038\n", "\n", "\n", "\n", "\n", "" ], "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.core.display import SVG\n", "\n", "SVG(filename=imageFileName+'.svg')" ] }, { "cell_type": "code", "execution_count": null, "id": "VsVRTs8WYSEA", "metadata": { "id": "VsVRTs8WYSEA" }, "outputs": [], "source": [] } ], "metadata": { "colab": { "provenance": [] }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.12" } }, "nbformat": 4, "nbformat_minor": 5 }