diff --git a/notebooks/GO/Edge-IC-Analysis.ipynb b/notebooks/GO/Edge-IC-Analysis.ipynb new file mode 100644 index 000000000..d829fe6de --- /dev/null +++ b/notebooks/GO/Edge-IC-Analysis.ipynb @@ -0,0 +1,718 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "initial_id", + "metadata": { + "collapsed": true, + "ExecuteTime": { + "end_time": "2024-06-21T05:04:50.875093Z", + "start_time": "2024-06-21T05:04:49.008341Z" + } + }, + "outputs": [], + "source": [ + "from oaklib import get_adapter\n", + "from oaklib.utilities.associations.edge_information_util import associations_to_matrix\n", + "\n", + "\n", + "ont_adapter = get_adapter(\"sqlite:obo:go\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "outputs": [], + "source": [ + "taxa = [\"9606\", \"6239\", \"7955\", \"3702\", \"559292\", \"4896\", \"7227\", \"10090\", \"ALL\"]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:21.601619Z", + "start_time": "2024-06-21T05:35:21.593149Z" + } + }, + "id": "5ff92fe5a9bcbbda" + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "collapsed": false + }, + "id": "21a08e783e48019e" + }, + { + "cell_type": "code", + "execution_count": 31, + "outputs": [], + "source": [ + "ic_map_by_taxon = {}\n", + "for tax in taxa:\n", + " n = f\"amigo:NCBITaxon:{tax}\" if tax != \"ALL\" else \"amigo:\"\n", + " assoc_adapter = get_adapter(n)\n", + " ic_map = {term: ic for term, ic in assoc_adapter.information_content_scores(use_associations=True)}\n", + " ic_map_by_taxon[tax] = ic_map" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:25.595141Z", + "start_time": "2024-06-21T05:35:23.166429Z" + } + }, + "id": "f0196639fef3e874" + }, + { + "cell_type": "code", + "execution_count": 32, + "outputs": [ + { + "data": { + "text/plain": "9" + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(ic_map_by_taxon)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:25.603072Z", + "start_time": "2024-06-21T05:35:25.596564Z" + } + }, + "id": "f3d95aa29e00f78" + }, + { + "cell_type": "code", + "execution_count": 33, + "outputs": [], + "source": [ + "from typing import Dict\n", + "\n", + "\n", + "def calculate_edge_information(child: str, parent: str, ic_map: Dict[str, float]):\n", + " if child not in ic_map or parent not in ic_map:\n", + " return None\n", + " child_ic = ic_map[child]\n", + " parent_ic = ic_map[parent]\n", + " return child_ic - parent_ic" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:28.127450Z", + "start_time": "2024-06-21T05:35:28.118170Z" + } + }, + "id": "363d0d6676c2c39b" + }, + { + "cell_type": "code", + "execution_count": 33, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:28.762205Z", + "start_time": "2024-06-21T05:35:28.754832Z" + } + }, + "id": "b303c5da2f0dca38" + }, + { + "cell_type": "code", + "execution_count": 34, + "outputs": [], + "source": [ + "c=\"GO:0008527\"\n", + "p=\"GO:0050912\"\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:29.512008Z", + "start_time": "2024-06-21T05:35:29.482125Z" + } + }, + "id": "9a287e3fe19ea32c" + }, + { + "cell_type": "code", + "execution_count": 35, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9606 0.6844981742720702\n", + "6239 None\n", + "7955 0.16992500144231393\n", + "3702 None\n", + "559292 None\n", + "4896 None\n", + "7227 0.15919859484925425\n", + "10090 0.405992359675837\n", + "ALL 0.360008134132741\n" + ] + } + ], + "source": [ + "for tx, matrix in ic_map_by_taxon.items():\n", + " print(tx, calculate_edge_information(c, p, matrix))" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:30.078176Z", + "start_time": "2024-06-21T05:35:30.070758Z" + } + }, + "id": "5bfcb4729b183682" + }, + { + "cell_type": "code", + "execution_count": 36, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'child': 'GO:0007563', 'parent': 'GO:2000026', 'predicate': 'rdfs:subClassOf', '9606': None, '6239': None, '7955': None, '3702': None, '559292': None, '4896': None, '7227': 5.357552004618083, '10090': None, 'ALL': 10.822457022324627}\n", + "{'child': 'GO:0019356', 'parent': 'GO:0019357', 'predicate': 'rdfs:subClassOf', '9606': None, '6239': None, '7955': None, '3702': None, '559292': None, '4896': None, '7227': None, '10090': None, 'ALL': None}\n", + "{'child': 'GO:0034346', 'parent': 'GO:0034343', 'predicate': 'RO:0002213', '9606': 0.0, '6239': None, '7955': None, '3702': None, '559292': None, '4896': None, '7227': None, '10090': 0.0, 'ALL': 0.0}\n", + "{'child': 'GO:0045831', 'parent': 'GO:0010461', 'predicate': 'RO:0002212', '9606': None, '6239': None, '7955': None, '3702': None, '559292': None, '4896': None, '7227': None, '10090': None, 'ALL': None}\n", + "{'child': 'GO:0060295', 'parent': 'GO:0003352', 'predicate': 'rdfs:subClassOf', '9606': 0.4381211123918849, '6239': 0.0, '7955': 0.5405683813627036, '3702': None, '559292': None, '4896': None, '7227': 1.8073549220576037, '10090': 0.40439025507933657, 'ALL': 0.5629361943911579}\n", + "{'child': 'GO:0090033', 'parent': 'GO:0045927', 'predicate': 'rdfs:subClassOf', '9606': None, '6239': None, '7955': None, '3702': None, '559292': 0.11103131238874298, '4896': None, '7227': None, '10090': None, 'ALL': 1.6593675666537084}\n", + "{'child': 'GO:1900362', 'parent': 'GO:0051050', 'predicate': 'rdfs:subClassOf', '9606': None, '6239': None, '7955': None, '3702': None, '559292': None, '4896': None, '7227': None, '10090': None, 'ALL': None}\n", + "{'child': 'GO:1904333', 'parent': 'GO:2000573', 'predicate': 'rdfs:subClassOf', '9606': 6.10852445677817, '6239': 0.32192809488736174, '7955': None, '3702': None, '559292': None, '4896': None, '7227': None, '10090': None, 'ALL': 6.62935662007961}\n" + ] + } + ], + "source": [ + "rows = []\n", + "for s, p, o in ont_adapter.relationships():\n", + " if not s.startswith(\"GO:\"):\n", + " continue\n", + " if not o.startswith(\"GO:\"):\n", + " continue\n", + " row = {\"child\": s, \"parent\": o, \"predicate\": p}\n", + " for t, matrix in ic_map_by_taxon.items():\n", + " v = calculate_edge_information(s, o, matrix)\n", + " row[t] = v\n", + " rows.append(row)\n", + " if len(rows) % 10000 == 0:\n", + " print(row)\n", + " " + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:37.782104Z", + "start_time": "2024-06-21T05:35:31.207240Z" + } + }, + "id": "3234ab59d5764c9e" + }, + { + "cell_type": "code", + "execution_count": 37, + "outputs": [], + "source": [ + "import pandas as pd\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:37.787700Z", + "start_time": "2024-06-21T05:35:37.782831Z" + } + }, + "id": "b196c3c52b341b7f" + }, + { + "cell_type": "code", + "execution_count": 38, + "outputs": [], + "source": [ + "def has_val(row: dict):\n", + " for k, v in row.items():\n", + " if k not in [\"child\", \"parent\", \"predicate\"]:\n", + " if v is not None:\n", + " return True\n", + " return False" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:37.793363Z", + "start_time": "2024-06-21T05:35:37.787311Z" + } + }, + "id": "20222d40e7efd529" + }, + { + "cell_type": "code", + "execution_count": 39, + "outputs": [], + "source": [ + "filtered_rows = [r for r in rows if has_val(r)]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:35:37.883685Z", + "start_time": "2024-06-21T05:35:37.804664Z" + } + }, + "id": "3587837f8196bfe4" + }, + { + "cell_type": "code", + "execution_count": 40, + "outputs": [], + "source": [ + "for row in filtered_rows:\n", + " row[\"child_label\"] = ont_adapter.label(row[\"child\"])\n", + " row[\"parent_label\"] = ont_adapter.label(row[\"parent\"])" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:36:00.243164Z", + "start_time": "2024-06-21T05:35:37.880294Z" + } + }, + "id": "d8210aebbcf8347a" + }, + { + "cell_type": "code", + "execution_count": 54, + "outputs": [ + { + "data": { + "text/plain": " child parent predicate 9606 6239 7955 \\\n0 GO:0000001 GO:0005739 obo:GOREL_0002003 NaN NaN NaN \n1 GO:0000001 GO:0048308 rdfs:subClassOf NaN NaN NaN \n2 GO:0000001 GO:0048311 rdfs:subClassOf NaN NaN NaN \n3 GO:0000002 GO:0007005 rdfs:subClassOf 4.056831 4.38247 4.551796 \n4 GO:0000006 GO:0005385 rdfs:subClassOf NaN NaN NaN \n... ... ... ... ... ... ... \n65831 GO:2001316 GO:0120254 rdfs:subClassOf NaN NaN NaN \n65832 GO:2001317 GO:0034309 rdfs:subClassOf NaN NaN NaN \n65833 GO:2001317 GO:0042181 rdfs:subClassOf NaN NaN NaN \n65834 GO:2001317 GO:0120255 rdfs:subClassOf NaN NaN NaN \n65835 GO:2001317 GO:2001316 rdfs:subClassOf NaN NaN NaN \n\n 3702 559292 4896 7227 10090 ALL \\\n0 NaN 5.872605 8.577429 7.812177 NaN 9.414945 \n1 NaN 1.373458 0.584963 0.000000 NaN 1.982152 \n2 NaN 0.241008 1.807355 1.459432 NaN 1.942707 \n3 3.658211 2.390915 2.929611 4.650254 3.865499 3.703148 \n4 NaN 3.169925 2.584963 NaN NaN 7.229558 \n... ... ... ... ... ... ... \n65831 NaN NaN NaN NaN NaN 9.466926 \n65832 NaN NaN NaN NaN NaN 7.176589 \n65833 NaN NaN NaN NaN NaN 9.716534 \n65834 NaN NaN NaN NaN NaN 6.481127 \n65835 NaN NaN NaN NaN NaN 0.000000 \n\n child_label \\\n0 mitochondrion inheritance \n1 mitochondrion inheritance \n2 mitochondrion inheritance \n3 mitochondrial genome maintenance \n4 high-affinity zinc transmembrane transporter a... \n... ... \n65831 kojic acid metabolic process \n65832 kojic acid biosynthetic process \n65833 kojic acid biosynthetic process \n65834 kojic acid biosynthetic process \n65835 kojic acid biosynthetic process \n\n parent_label \n0 mitochondrion \n1 organelle inheritance \n2 mitochondrion distribution \n3 mitochondrion organization \n4 zinc ion transmembrane transporter activity \n... ... \n65831 olefinic compound metabolic process \n65832 primary alcohol biosynthetic process \n65833 ketone biosynthetic process \n65834 olefinic compound biosynthetic process \n65835 kojic acid metabolic process \n\n[65836 rows x 14 columns]", + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
childparentpredicate96066239795537025592924896722710090ALLchild_labelparent_label
0GO:0000001GO:0005739obo:GOREL_0002003NaNNaNNaNNaN5.8726058.5774297.812177NaN9.414945mitochondrion inheritancemitochondrion
1GO:0000001GO:0048308rdfs:subClassOfNaNNaNNaNNaN1.3734580.5849630.000000NaN1.982152mitochondrion inheritanceorganelle inheritance
2GO:0000001GO:0048311rdfs:subClassOfNaNNaNNaNNaN0.2410081.8073551.459432NaN1.942707mitochondrion inheritancemitochondrion distribution
3GO:0000002GO:0007005rdfs:subClassOf4.0568314.382474.5517963.6582112.3909152.9296114.6502543.8654993.703148mitochondrial genome maintenancemitochondrion organization
4GO:0000006GO:0005385rdfs:subClassOfNaNNaNNaNNaN3.1699252.584963NaNNaN7.229558high-affinity zinc transmembrane transporter a...zinc ion transmembrane transporter activity
.............................................
65831GO:2001316GO:0120254rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN9.466926kojic acid metabolic processolefinic compound metabolic process
65832GO:2001317GO:0034309rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN7.176589kojic acid biosynthetic processprimary alcohol biosynthetic process
65833GO:2001317GO:0042181rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN9.716534kojic acid biosynthetic processketone biosynthetic process
65834GO:2001317GO:0120255rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN6.481127kojic acid biosynthetic processolefinic compound biosynthetic process
65835GO:2001317GO:2001316rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.000000kojic acid biosynthetic processkojic acid metabolic process
\n

65836 rows × 14 columns

\n
" + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(filtered_rows)\n", + "df" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:37:40.790335Z", + "start_time": "2024-06-21T05:37:40.712016Z" + } + }, + "id": "ae6bae32526f09ad" + }, + { + "cell_type": "code", + "execution_count": 55, + "outputs": [], + "source": [ + "!mkdir -p results" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:37:41.881905Z", + "start_time": "2024-06-21T05:37:41.722310Z" + } + }, + "id": "fb27ed2f8067b8e0" + }, + { + "cell_type": "code", + "execution_count": 56, + "outputs": [], + "source": [ + "df.to_csv(\"results/edge_information.csv\", index=False)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:37:43.073543Z", + "start_time": "2024-06-21T05:37:42.439067Z" + } + }, + "id": "b3443f3e443af550" + }, + { + "cell_type": "code", + "execution_count": 57, + "outputs": [], + "source": [ + "taxa_columns = df.columns[3:-2]\n", + "species_columns = df.columns[3:-3]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:37:43.285612Z", + "start_time": "2024-06-21T05:37:43.277592Z" + } + }, + "id": "33fc513d1090313a" + }, + { + "cell_type": "code", + "execution_count": 58, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/nc/m4tx21912kv1b8nk3zzx9plr0000gn/T/ipykernel_39537/3033132071.py:4: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n", + " df[taxa_columns] = df[taxa_columns].applymap(lambda x: np.nan if x < 0 else x)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "\n", + "# Replace negative ICdiff values with NaN (treated as None)\n", + "df[taxa_columns] = df[taxa_columns].applymap(lambda x: np.nan if x < 0 else x)\n", + "\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:37:44.117886Z", + "start_time": "2024-06-21T05:37:44.004567Z" + } + }, + "id": "676e7d015135b3d0" + }, + { + "cell_type": "code", + "execution_count": 59, + "outputs": [], + "source": [ + "# Recalculate the average ICdiff for each edge\n", + "df['average_ICdiff'] = df[taxa_columns].mean(axis=1, skipna=True)\n", + "df['average_ICdiff_sp'] = df[species_columns].mean(axis=1, skipna=True)\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:38:08.098887Z", + "start_time": "2024-06-21T05:38:08.069456Z" + } + }, + "id": "4261e3a9d8dc5b5" + }, + { + "cell_type": "code", + "execution_count": 60, + "outputs": [], + "source": [ + "# Recalculate the maximum ICdiff for each edge\n", + "df['max_ICdiff'] = df[taxa_columns].max(axis=1, skipna=True)\n", + "df['max_ICdiff_sp'] = df[species_columns].max(axis=1, skipna=True)\n", + "\n", + "# Identify edges with the lowest average ICdiff\n", + "lowest_average_ICdiff_edges = df.loc[df['average_ICdiff'] == df['average_ICdiff'].min()]\n", + "\n", + "# Identify edges with the lowest maximum ICdiff\n", + "lowest_max_ICdiff_edges = df.loc[df['max_ICdiff'] == df['max_ICdiff'].min()]\n", + "\n", + "# Results\n", + "low_icdiff_stats = {\n", + " 'lowest_average_ICdiff_edges': lowest_average_ICdiff_edges,\n", + " 'lowest_max_ICdiff_edges': lowest_max_ICdiff_edges,\n", + " 'average_ICdiff_per_edge': df[['child', 'parent', 'predicate', 'average_ICdiff']],\n", + " 'max_ICdiff_per_edge': df[['child', 'parent', 'predicate', 'max_ICdiff']]\n", + "}" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:38:31.414470Z", + "start_time": "2024-06-21T05:38:31.382296Z" + } + }, + "id": "370871dfa091dc83" + }, + { + "cell_type": "code", + "execution_count": 61, + "outputs": [ + { + "data": { + "text/plain": "{'lowest_average_ICdiff_edges': child parent predicate 9606 6239 7955 3702 \\\n 49 GO:0000036 GO:0044620 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n 50 GO:0000036 GO:0140414 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n 88 GO:0000073 GO:1905047 BFO:0000050 NaN NaN NaN NaN \n 89 GO:0000073 GO:0110100 rdfs:subClassOf NaN NaN NaN NaN \n 100 GO:0000080 GO:0051318 rdfs:subClassOf 0.0 NaN NaN 0.0 \n ... ... ... ... ... ... ... ... \n 65782 GO:2001299 GO:2001298 rdfs:subClassOf 0.0 NaN NaN NaN \n 65806 GO:2001307 GO:2001305 rdfs:subClassOf NaN NaN NaN NaN \n 65820 GO:2001310 GO:2001308 rdfs:subClassOf NaN NaN NaN NaN \n 65828 GO:2001315 GO:2001313 rdfs:subClassOf NaN NaN NaN NaN \n 65835 GO:2001317 GO:2001316 rdfs:subClassOf NaN NaN NaN NaN \n \n 559292 4896 7227 10090 ALL \\\n 49 0.0 0.0 0.0 0.0 0.0 \n 50 0.0 0.0 0.0 0.0 0.0 \n 88 0.0 0.0 NaN NaN 0.0 \n 89 0.0 0.0 NaN NaN 0.0 \n 100 0.0 NaN NaN 0.0 0.0 \n ... ... ... ... ... ... \n 65782 NaN NaN NaN 0.0 0.0 \n 65806 NaN NaN NaN NaN 0.0 \n 65820 NaN NaN NaN NaN 0.0 \n 65828 NaN NaN NaN NaN 0.0 \n 65835 NaN NaN NaN NaN 0.0 \n \n child_label \\\n 49 acyl carrier activity \n 50 acyl carrier activity \n 88 initial mitotic spindle pole body separation \n 89 initial mitotic spindle pole body separation \n 100 mitotic G1 phase \n ... ... \n 65782 N(omega),N(omega)-dimethyl-L-arginine cataboli... \n 65806 xanthone-containing compound biosynthetic process \n 65820 gliotoxin biosynthetic process \n 65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... \n 65835 kojic acid biosynthetic process \n \n parent_label average_ICdiff \\\n 49 ACP phosphopantetheine attachment site binding 0.0 \n 50 phosphopantetheine-dependent carrier activity 0.0 \n 88 mitotic spindle pole body organization 0.0 \n 89 spindle pole body separation 0.0 \n 100 G1 phase 0.0 \n ... ... ... \n 65782 N(omega),N(omega)-dimethyl-L-arginine metaboli... 0.0 \n 65806 xanthone-containing compound metabolic process 0.0 \n 65820 gliotoxin metabolic process 0.0 \n 65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... 0.0 \n 65835 kojic acid metabolic process 0.0 \n \n average_ICdiff_sp max_ICdiff max_ICdiff_sp \n 49 0.0 0.0 0.0 \n 50 0.0 0.0 0.0 \n 88 0.0 0.0 0.0 \n 89 0.0 0.0 0.0 \n 100 0.0 0.0 0.0 \n ... ... ... ... \n 65782 0.0 0.0 0.0 \n 65806 NaN 0.0 NaN \n 65820 NaN 0.0 NaN \n 65828 NaN 0.0 NaN \n 65835 NaN 0.0 NaN \n \n [2259 rows x 18 columns],\n 'lowest_max_ICdiff_edges': child parent predicate 9606 6239 7955 3702 \\\n 49 GO:0000036 GO:0044620 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n 50 GO:0000036 GO:0140414 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n 88 GO:0000073 GO:1905047 BFO:0000050 NaN NaN NaN NaN \n 89 GO:0000073 GO:0110100 rdfs:subClassOf NaN NaN NaN NaN \n 100 GO:0000080 GO:0051318 rdfs:subClassOf 0.0 NaN NaN 0.0 \n ... ... ... ... ... ... ... ... \n 65782 GO:2001299 GO:2001298 rdfs:subClassOf 0.0 NaN NaN NaN \n 65806 GO:2001307 GO:2001305 rdfs:subClassOf NaN NaN NaN NaN \n 65820 GO:2001310 GO:2001308 rdfs:subClassOf NaN NaN NaN NaN \n 65828 GO:2001315 GO:2001313 rdfs:subClassOf NaN NaN NaN NaN \n 65835 GO:2001317 GO:2001316 rdfs:subClassOf NaN NaN NaN NaN \n \n 559292 4896 7227 10090 ALL \\\n 49 0.0 0.0 0.0 0.0 0.0 \n 50 0.0 0.0 0.0 0.0 0.0 \n 88 0.0 0.0 NaN NaN 0.0 \n 89 0.0 0.0 NaN NaN 0.0 \n 100 0.0 NaN NaN 0.0 0.0 \n ... ... ... ... ... ... \n 65782 NaN NaN NaN 0.0 0.0 \n 65806 NaN NaN NaN NaN 0.0 \n 65820 NaN NaN NaN NaN 0.0 \n 65828 NaN NaN NaN NaN 0.0 \n 65835 NaN NaN NaN NaN 0.0 \n \n child_label \\\n 49 acyl carrier activity \n 50 acyl carrier activity \n 88 initial mitotic spindle pole body separation \n 89 initial mitotic spindle pole body separation \n 100 mitotic G1 phase \n ... ... \n 65782 N(omega),N(omega)-dimethyl-L-arginine cataboli... \n 65806 xanthone-containing compound biosynthetic process \n 65820 gliotoxin biosynthetic process \n 65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... \n 65835 kojic acid biosynthetic process \n \n parent_label average_ICdiff \\\n 49 ACP phosphopantetheine attachment site binding 0.0 \n 50 phosphopantetheine-dependent carrier activity 0.0 \n 88 mitotic spindle pole body organization 0.0 \n 89 spindle pole body separation 0.0 \n 100 G1 phase 0.0 \n ... ... ... \n 65782 N(omega),N(omega)-dimethyl-L-arginine metaboli... 0.0 \n 65806 xanthone-containing compound metabolic process 0.0 \n 65820 gliotoxin metabolic process 0.0 \n 65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... 0.0 \n 65835 kojic acid metabolic process 0.0 \n \n average_ICdiff_sp max_ICdiff max_ICdiff_sp \n 49 0.0 0.0 0.0 \n 50 0.0 0.0 0.0 \n 88 0.0 0.0 0.0 \n 89 0.0 0.0 0.0 \n 100 0.0 0.0 0.0 \n ... ... ... ... \n 65782 0.0 0.0 0.0 \n 65806 NaN 0.0 NaN \n 65820 NaN 0.0 NaN \n 65828 NaN 0.0 NaN \n 65835 NaN 0.0 NaN \n \n [2259 rows x 18 columns],\n 'average_ICdiff_per_edge': child parent predicate average_ICdiff\n 0 GO:0000001 GO:0005739 obo:GOREL_0002003 7.919289\n 1 GO:0000001 GO:0048308 rdfs:subClassOf 0.985143\n 2 GO:0000001 GO:0048311 rdfs:subClassOf 1.362625\n 3 GO:0000002 GO:0007005 rdfs:subClassOf 3.798748\n 4 GO:0000006 GO:0005385 rdfs:subClassOf 4.328149\n ... ... ... ... ...\n 65831 GO:2001316 GO:0120254 rdfs:subClassOf 9.466926\n 65832 GO:2001317 GO:0034309 rdfs:subClassOf 7.176589\n 65833 GO:2001317 GO:0042181 rdfs:subClassOf 9.716534\n 65834 GO:2001317 GO:0120255 rdfs:subClassOf 6.481127\n 65835 GO:2001317 GO:2001316 rdfs:subClassOf 0.000000\n \n [65836 rows x 4 columns],\n 'max_ICdiff_per_edge': child parent predicate max_ICdiff\n 0 GO:0000001 GO:0005739 obo:GOREL_0002003 9.414945\n 1 GO:0000001 GO:0048308 rdfs:subClassOf 1.982152\n 2 GO:0000001 GO:0048311 rdfs:subClassOf 1.942707\n 3 GO:0000002 GO:0007005 rdfs:subClassOf 4.650254\n 4 GO:0000006 GO:0005385 rdfs:subClassOf 7.229558\n ... ... ... ... ...\n 65831 GO:2001316 GO:0120254 rdfs:subClassOf 9.466926\n 65832 GO:2001317 GO:0034309 rdfs:subClassOf 7.176589\n 65833 GO:2001317 GO:0042181 rdfs:subClassOf 9.716534\n 65834 GO:2001317 GO:0120255 rdfs:subClassOf 6.481127\n 65835 GO:2001317 GO:2001316 rdfs:subClassOf 0.000000\n \n [65836 rows x 4 columns]}" + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "low_icdiff_stats" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:38:32.379761Z", + "start_time": "2024-06-21T05:38:32.353337Z" + } + }, + "id": "f43fd479b14bb694" + }, + { + "cell_type": "code", + "execution_count": 62, + "outputs": [ + { + "data": { + "text/plain": " child parent predicate 9606 6239 7955 \\\n0 GO:0000001 GO:0005739 obo:GOREL_0002003 NaN NaN NaN \n1 GO:0000001 GO:0048308 rdfs:subClassOf NaN NaN NaN \n2 GO:0000001 GO:0048311 rdfs:subClassOf NaN NaN NaN \n3 GO:0000002 GO:0007005 rdfs:subClassOf 4.056831 4.38247 4.551796 \n4 GO:0000006 GO:0005385 rdfs:subClassOf NaN NaN NaN \n... ... ... ... ... ... ... \n65831 GO:2001316 GO:0120254 rdfs:subClassOf NaN NaN NaN \n65832 GO:2001317 GO:0034309 rdfs:subClassOf NaN NaN NaN \n65833 GO:2001317 GO:0042181 rdfs:subClassOf NaN NaN NaN \n65834 GO:2001317 GO:0120255 rdfs:subClassOf NaN NaN NaN \n65835 GO:2001317 GO:2001316 rdfs:subClassOf NaN NaN NaN \n\n 3702 559292 4896 7227 10090 ALL \\\n0 NaN 5.872605 8.577429 7.812177 NaN 9.414945 \n1 NaN 1.373458 0.584963 0.000000 NaN 1.982152 \n2 NaN 0.241008 1.807355 1.459432 NaN 1.942707 \n3 3.658211 2.390915 2.929611 4.650254 3.865499 3.703148 \n4 NaN 3.169925 2.584963 NaN NaN 7.229558 \n... ... ... ... ... ... ... \n65831 NaN NaN NaN NaN NaN 9.466926 \n65832 NaN NaN NaN NaN NaN 7.176589 \n65833 NaN NaN NaN NaN NaN 9.716534 \n65834 NaN NaN NaN NaN NaN 6.481127 \n65835 NaN NaN NaN NaN NaN 0.000000 \n\n child_label \\\n0 mitochondrion inheritance \n1 mitochondrion inheritance \n2 mitochondrion inheritance \n3 mitochondrial genome maintenance \n4 high-affinity zinc transmembrane transporter a... \n... ... \n65831 kojic acid metabolic process \n65832 kojic acid biosynthetic process \n65833 kojic acid biosynthetic process \n65834 kojic acid biosynthetic process \n65835 kojic acid biosynthetic process \n\n parent_label average_ICdiff \\\n0 mitochondrion 7.919289 \n1 organelle inheritance 0.985143 \n2 mitochondrion distribution 1.362625 \n3 mitochondrion organization 3.798748 \n4 zinc ion transmembrane transporter activity 4.328149 \n... ... ... \n65831 olefinic compound metabolic process 9.466926 \n65832 primary alcohol biosynthetic process 7.176589 \n65833 ketone biosynthetic process 9.716534 \n65834 olefinic compound biosynthetic process 6.481127 \n65835 kojic acid metabolic process 0.000000 \n\n average_ICdiff_sp max_ICdiff max_ICdiff_sp \n0 7.420737 9.414945 8.577429 \n1 0.652807 1.982152 1.373458 \n2 1.169265 1.942707 1.807355 \n3 3.810698 4.650254 4.650254 \n4 2.877444 7.229558 3.169925 \n... ... ... ... \n65831 NaN 9.466926 NaN \n65832 NaN 7.176589 NaN \n65833 NaN 9.716534 NaN \n65834 NaN 6.481127 NaN \n65835 NaN 0.000000 NaN \n\n[65836 rows x 18 columns]", + "text/html": "
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childparentpredicate96066239795537025592924896722710090ALLchild_labelparent_labelaverage_ICdiffaverage_ICdiff_spmax_ICdiffmax_ICdiff_sp
0GO:0000001GO:0005739obo:GOREL_0002003NaNNaNNaNNaN5.8726058.5774297.812177NaN9.414945mitochondrion inheritancemitochondrion7.9192897.4207379.4149458.577429
1GO:0000001GO:0048308rdfs:subClassOfNaNNaNNaNNaN1.3734580.5849630.000000NaN1.982152mitochondrion inheritanceorganelle inheritance0.9851430.6528071.9821521.373458
2GO:0000001GO:0048311rdfs:subClassOfNaNNaNNaNNaN0.2410081.8073551.459432NaN1.942707mitochondrion inheritancemitochondrion distribution1.3626251.1692651.9427071.807355
3GO:0000002GO:0007005rdfs:subClassOf4.0568314.382474.5517963.6582112.3909152.9296114.6502543.8654993.703148mitochondrial genome maintenancemitochondrion organization3.7987483.8106984.6502544.650254
4GO:0000006GO:0005385rdfs:subClassOfNaNNaNNaNNaN3.1699252.584963NaNNaN7.229558high-affinity zinc transmembrane transporter a...zinc ion transmembrane transporter activity4.3281492.8774447.2295583.169925
.........................................................
65831GO:2001316GO:0120254rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN9.466926kojic acid metabolic processolefinic compound metabolic process9.466926NaN9.466926NaN
65832GO:2001317GO:0034309rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN7.176589kojic acid biosynthetic processprimary alcohol biosynthetic process7.176589NaN7.176589NaN
65833GO:2001317GO:0042181rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN9.716534kojic acid biosynthetic processketone biosynthetic process9.716534NaN9.716534NaN
65834GO:2001317GO:0120255rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN6.481127kojic acid biosynthetic processolefinic compound biosynthetic process6.481127NaN6.481127NaN
65835GO:2001317GO:2001316rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.000000kojic acid biosynthetic processkojic acid metabolic process0.000000NaN0.000000NaN
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65836 rows × 18 columns

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" + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:38:33.774083Z", + "start_time": "2024-06-21T05:38:33.766922Z" + } + }, + "id": "c3d312d2641042f6" + }, + { + "cell_type": "code", + "execution_count": 63, + "outputs": [ + { + "data": { + "text/plain": " child parent predicate 9606 6239 7955 3702 \\\n49 GO:0000036 GO:0044620 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n50 GO:0000036 GO:0140414 rdfs:subClassOf 0.0 0.0 0.0 0.0 \n88 GO:0000073 GO:1905047 BFO:0000050 NaN NaN NaN NaN \n89 GO:0000073 GO:0110100 rdfs:subClassOf NaN NaN NaN NaN \n100 GO:0000080 GO:0051318 rdfs:subClassOf 0.0 NaN NaN 0.0 \n... ... ... ... ... ... ... ... \n65782 GO:2001299 GO:2001298 rdfs:subClassOf 0.0 NaN NaN NaN \n65806 GO:2001307 GO:2001305 rdfs:subClassOf NaN NaN NaN NaN \n65820 GO:2001310 GO:2001308 rdfs:subClassOf NaN NaN NaN NaN \n65828 GO:2001315 GO:2001313 rdfs:subClassOf NaN NaN NaN NaN \n65835 GO:2001317 GO:2001316 rdfs:subClassOf NaN NaN NaN NaN \n\n 559292 4896 7227 10090 ALL \\\n49 0.0 0.0 0.0 0.0 0.0 \n50 0.0 0.0 0.0 0.0 0.0 \n88 0.0 0.0 NaN NaN 0.0 \n89 0.0 0.0 NaN NaN 0.0 \n100 0.0 NaN NaN 0.0 0.0 \n... ... ... ... ... ... \n65782 NaN NaN NaN 0.0 0.0 \n65806 NaN NaN NaN NaN 0.0 \n65820 NaN NaN NaN NaN 0.0 \n65828 NaN NaN NaN NaN 0.0 \n65835 NaN NaN NaN NaN 0.0 \n\n child_label \\\n49 acyl carrier activity \n50 acyl carrier activity \n88 initial mitotic spindle pole body separation \n89 initial mitotic spindle pole body separation \n100 mitotic G1 phase \n... ... \n65782 N(omega),N(omega)-dimethyl-L-arginine cataboli... \n65806 xanthone-containing compound biosynthetic process \n65820 gliotoxin biosynthetic process \n65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... \n65835 kojic acid biosynthetic process \n\n parent_label average_ICdiff \\\n49 ACP phosphopantetheine attachment site binding 0.0 \n50 phosphopantetheine-dependent carrier activity 0.0 \n88 mitotic spindle pole body organization 0.0 \n89 spindle pole body separation 0.0 \n100 G1 phase 0.0 \n... ... ... \n65782 N(omega),N(omega)-dimethyl-L-arginine metaboli... 0.0 \n65806 xanthone-containing compound metabolic process 0.0 \n65820 gliotoxin metabolic process 0.0 \n65828 UDP-4-deoxy-4-formamido-beta-L-arabinopyranose... 0.0 \n65835 kojic acid metabolic process 0.0 \n\n average_ICdiff_sp max_ICdiff max_ICdiff_sp \n49 0.0 0.0 0.0 \n50 0.0 0.0 0.0 \n88 0.0 0.0 0.0 \n89 0.0 0.0 0.0 \n100 0.0 0.0 0.0 \n... ... ... ... \n65782 0.0 0.0 0.0 \n65806 NaN 0.0 NaN \n65820 NaN 0.0 NaN \n65828 NaN 0.0 NaN \n65835 NaN 0.0 NaN \n\n[2259 rows x 18 columns]", + "text/html": "
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childparentpredicate96066239795537025592924896722710090ALLchild_labelparent_labelaverage_ICdiffaverage_ICdiff_spmax_ICdiffmax_ICdiff_sp
49GO:0000036GO:0044620rdfs:subClassOf0.00.00.00.00.00.00.00.00.0acyl carrier activityACP phosphopantetheine attachment site binding0.00.00.00.0
50GO:0000036GO:0140414rdfs:subClassOf0.00.00.00.00.00.00.00.00.0acyl carrier activityphosphopantetheine-dependent carrier activity0.00.00.00.0
88GO:0000073GO:1905047BFO:0000050NaNNaNNaNNaN0.00.0NaNNaN0.0initial mitotic spindle pole body separationmitotic spindle pole body organization0.00.00.00.0
89GO:0000073GO:0110100rdfs:subClassOfNaNNaNNaNNaN0.00.0NaNNaN0.0initial mitotic spindle pole body separationspindle pole body separation0.00.00.00.0
100GO:0000080GO:0051318rdfs:subClassOf0.0NaNNaN0.00.0NaNNaN0.00.0mitotic G1 phaseG1 phase0.00.00.00.0
.........................................................
65782GO:2001299GO:2001298rdfs:subClassOf0.0NaNNaNNaNNaNNaNNaN0.00.0N(omega),N(omega)-dimethyl-L-arginine cataboli...N(omega),N(omega)-dimethyl-L-arginine metaboli...0.00.00.00.0
65806GO:2001307GO:2001305rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.0xanthone-containing compound biosynthetic processxanthone-containing compound metabolic process0.0NaN0.0NaN
65820GO:2001310GO:2001308rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.0gliotoxin biosynthetic processgliotoxin metabolic process0.0NaN0.0NaN
65828GO:2001315GO:2001313rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.0UDP-4-deoxy-4-formamido-beta-L-arabinopyranose...UDP-4-deoxy-4-formamido-beta-L-arabinopyranose...0.0NaN0.0NaN
65835GO:2001317GO:2001316rdfs:subClassOfNaNNaNNaNNaNNaNNaNNaNNaN0.0kojic acid biosynthetic processkojic acid metabolic process0.0NaN0.0NaN
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2259 rows × 18 columns

\n
" + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[df[\"max_ICdiff\"] == 0]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:38:42.707730Z", + "start_time": "2024-06-21T05:38:42.685154Z" + } + }, + "id": "d535033c8e457b85" + }, + { + "cell_type": "code", + "execution_count": 51, + "outputs": [], + "source": [ + "df[df[\"max_ICdiff\"] == 0].to_csv(\"results/edge_information_zero_ICdiff.csv\", index=False)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:36:01.424102Z", + "start_time": "2024-06-21T05:36:01.360689Z" + } + }, + "id": "2f6e3b54bc2085bf" + }, + { + "cell_type": "code", + "execution_count": 69, + "outputs": [], + "source": [ + "sp_only = df[(df[\"max_ICdiff_sp\"] == 0) & (df[\"ALL\"] > 0)]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:47:32.162879Z", + "start_time": "2024-06-21T05:47:32.155883Z" + } + }, + "id": "e0798a0d7a84d811" + }, + { + "cell_type": "code", + "execution_count": 70, + "outputs": [ + { + "data": { + "text/plain": " child parent predicate 9606 6239 7955 3702 \\\n14 GO:0000015 GO:0004634 RO:0002215 0.0 0.0 0.0 0.0 \n42 GO:0000032 GO:0006057 rdfs:subClassOf NaN NaN NaN NaN \n43 GO:0000032 GO:0031506 rdfs:subClassOf NaN NaN NaN NaN \n111 GO:0000088 GO:0000087 BFO:0000050 NaN NaN NaN 0.0 \n113 GO:0000089 GO:0000087 BFO:0000050 NaN NaN NaN NaN \n... ... ... ... ... ... ... ... \n65629 GO:2001229 GO:2001228 rdfs:subClassOf NaN NaN NaN NaN \n65632 GO:2001230 GO:2001228 rdfs:subClassOf NaN 0.0 NaN NaN \n65690 GO:2001250 GO:0045848 rdfs:subClassOf 0.0 NaN NaN NaN \n65691 GO:2001250 GO:2000213 rdfs:subClassOf 0.0 NaN NaN NaN \n65804 GO:2001306 GO:2001304 rdfs:subClassOf 0.0 NaN NaN NaN \n\n 559292 4896 7227 10090 ALL \\\n14 0.0 0.0 0.0 0.0 0.048799 \n42 0.0 0.0 NaN NaN 0.078305 \n43 0.0 0.0 NaN NaN 0.011450 \n111 NaN NaN NaN NaN 3.954196 \n113 NaN NaN NaN 0.0 1.632268 \n... ... ... ... ... ... \n65629 NaN NaN 0.0 0.0 0.415037 \n65632 NaN NaN NaN NaN 2.000000 \n65690 NaN NaN NaN 0.0 0.459432 \n65691 NaN NaN NaN 0.0 1.584963 \n65804 NaN NaN NaN 0.0 0.222392 \n\n child_label \\\n14 phosphopyruvate hydratase complex \n42 cell wall mannoprotein biosynthetic process \n43 cell wall mannoprotein biosynthetic process \n111 mitotic prophase \n113 mitotic metaphase \n... ... \n65629 negative regulation of response to gamma radia... \n65632 positive regulation of response to gamma radia... \n65690 positive regulation of ammonia assimilation cycle \n65691 positive regulation of ammonia assimilation cycle \n65804 lipoxin B4 biosynthetic process \n\n parent_label average_ICdiff \\\n14 phosphopyruvate hydratase activity 0.005422 \n42 mannoprotein biosynthetic process 0.026102 \n43 cell wall glycoprotein biosynthetic process 0.003817 \n111 mitotic M phase 1.977098 \n113 mitotic M phase 0.816134 \n... ... ... \n65629 regulation of response to gamma radiation 0.138346 \n65632 regulation of response to gamma radiation 1.000000 \n65690 positive regulation of nitrogen utilization 0.153144 \n65691 positive regulation of glutamate metabolic pro... 0.528321 \n65804 lipoxin B4 metabolic process 0.074131 \n\n average_ICdiff_sp max_ICdiff max_ICdiff_sp \n14 0.0 0.048799 0.0 \n42 0.0 0.078305 0.0 \n43 0.0 0.011450 0.0 \n111 0.0 3.954196 0.0 \n113 0.0 1.632268 0.0 \n... ... ... ... \n65629 0.0 0.415037 0.0 \n65632 0.0 2.000000 0.0 \n65690 0.0 0.459432 0.0 \n65691 0.0 1.584963 0.0 \n65804 0.0 0.222392 0.0 \n\n[1717 rows x 18 columns]", + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
childparentpredicate96066239795537025592924896722710090ALLchild_labelparent_labelaverage_ICdiffaverage_ICdiff_spmax_ICdiffmax_ICdiff_sp
14GO:0000015GO:0004634RO:00022150.00.00.00.00.00.00.00.00.048799phosphopyruvate hydratase complexphosphopyruvate hydratase activity0.0054220.00.0487990.0
42GO:0000032GO:0006057rdfs:subClassOfNaNNaNNaNNaN0.00.0NaNNaN0.078305cell wall mannoprotein biosynthetic processmannoprotein biosynthetic process0.0261020.00.0783050.0
43GO:0000032GO:0031506rdfs:subClassOfNaNNaNNaNNaN0.00.0NaNNaN0.011450cell wall mannoprotein biosynthetic processcell wall glycoprotein biosynthetic process0.0038170.00.0114500.0
111GO:0000088GO:0000087BFO:0000050NaNNaNNaN0.0NaNNaNNaNNaN3.954196mitotic prophasemitotic M phase1.9770980.03.9541960.0
113GO:0000089GO:0000087BFO:0000050NaNNaNNaNNaNNaNNaNNaN0.01.632268mitotic metaphasemitotic M phase0.8161340.01.6322680.0
.........................................................
65629GO:2001229GO:2001228rdfs:subClassOfNaNNaNNaNNaNNaNNaN0.00.00.415037negative regulation of response to gamma radia...regulation of response to gamma radiation0.1383460.00.4150370.0
65632GO:2001230GO:2001228rdfs:subClassOfNaN0.0NaNNaNNaNNaNNaNNaN2.000000positive regulation of response to gamma radia...regulation of response to gamma radiation1.0000000.02.0000000.0
65690GO:2001250GO:0045848rdfs:subClassOf0.0NaNNaNNaNNaNNaNNaN0.00.459432positive regulation of ammonia assimilation cyclepositive regulation of nitrogen utilization0.1531440.00.4594320.0
65691GO:2001250GO:2000213rdfs:subClassOf0.0NaNNaNNaNNaNNaNNaN0.01.584963positive regulation of ammonia assimilation cyclepositive regulation of glutamate metabolic pro...0.5283210.01.5849630.0
65804GO:2001306GO:2001304rdfs:subClassOf0.0NaNNaNNaNNaNNaNNaN0.00.222392lipoxin B4 biosynthetic processlipoxin B4 metabolic process0.0741310.00.2223920.0
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" + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sp_only" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:47:33.294487Z", + "start_time": "2024-06-21T05:47:33.289970Z" + } + }, + "id": "57ac8efd625c99ee" + }, + { + "cell_type": "code", + "execution_count": 71, + "outputs": [], + "source": [ + "sp_only.to_csv(\"results/edge_information_zero_ICdiff_sp.csv\", index=False)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T05:47:36.356653Z", + "start_time": "2024-06-21T05:47:36.331179Z" + } + }, + "id": "8b9965a6dac3626b" + }, + { + "cell_type": "markdown", + "source": [ + "## Agreement between species" + ], + "metadata": { + "collapsed": false + }, + "id": "5ee6a7afd3525df1" + }, + { + "cell_type": "code", + "execution_count": 73, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pairwise Distance Matrix:\n", + " 9606 6239 7955 3702 559292 4896 7227 \\\n", + "9606 0.000000 0.521991 0.384054 0.643245 0.615788 0.637006 0.489546 \n", + "6239 0.521991 0.000000 0.378123 0.495840 0.478491 0.499582 0.331505 \n", + "7955 0.384054 0.378123 0.000000 0.555535 0.549247 0.566367 0.382261 \n", + "3702 0.643245 0.495840 0.555535 0.000000 0.481308 0.488853 0.536048 \n", + "559292 0.615788 0.478491 0.549247 0.481308 0.000000 0.313815 0.512179 \n", + "4896 0.637006 0.499582 0.566367 0.488853 0.313815 0.000000 0.525220 \n", + "7227 0.489546 0.331505 0.382261 0.536048 0.512179 0.525220 0.000000 \n", + "10090 0.077110 0.530687 0.392722 0.651923 0.627839 0.651838 0.500718 \n", + "ALL 0.341423 0.655647 0.562346 0.613442 0.668773 0.679804 0.594839 \n", + "\n", + " 10090 ALL \n", + "9606 0.077110 0.341423 \n", + "6239 0.530687 0.655647 \n", + "7955 0.392722 0.562346 \n", + "3702 0.651923 0.613442 \n", + "559292 0.627839 0.668773 \n", + "4896 0.651838 0.679804 \n", + "7227 0.500718 0.594839 \n", + "10090 0.000000 0.333682 \n", + "ALL 0.333682 0.000000 \n", + "The taxa pair with the highest disagreement is: ('4896', 'ALL') with a distance of 0.679803533659782\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "from scipy.spatial.distance import pdist, squareform\n", + "\n", + "\n", + "# Extract the taxa columns (assuming they are the columns with numeric names)\n", + "df = pd.DataFrame(filtered_rows)\n", + "taxa_columns = df.columns[3:-2]\n", + "\n", + "# Fill NaN values with column means for distance calculation\n", + "df_filled = df[taxa_columns].fillna(df[taxa_columns].mean())\n", + "\n", + "# Calculate pairwise distances between taxa using Pearson correlation distance\n", + "pairwise_distances = pdist(df_filled.T, metric='correlation')\n", + "\n", + "# Convert to a square matrix\n", + "pairwise_distances_matrix = squareform(pairwise_distances)\n", + "\n", + "# Create a DataFrame for better readability\n", + "taxa_pairwise_distances_df = pd.DataFrame(pairwise_distances_matrix, index=taxa_columns, columns=taxa_columns)\n", + "\n", + "# Identify the taxa pairs with the highest disagreement (largest distance)\n", + "max_disagreement = taxa_pairwise_distances_df.max().max()\n", + "max_disagreement_pair = taxa_pairwise_distances_df.stack().idxmax()\n", + "\n", + "# Display the results\n", + "print(\"Pairwise Distance Matrix:\")\n", + "print(taxa_pairwise_distances_df)\n", + "\n", + "print(f\"The taxa pair with the highest disagreement is: {max_disagreement_pair} with a distance of {max_disagreement}\")\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T06:58:50.897001Z", + "start_time": "2024-06-21T06:58:50.681973Z" + } + }, + "id": "8f61dec3c7990e4b" + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "826b483e80fdd613" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/GO/Edge-Information-Analysis.ipynb b/notebooks/GO/Edge-Information-Analysis.ipynb new file mode 100644 index 000000000..351ed6d4d --- /dev/null +++ b/notebooks/GO/Edge-Information-Analysis.ipynb @@ -0,0 +1,528 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 14, + "id": "initial_id", + "metadata": { + "collapsed": true, + "ExecuteTime": { + "end_time": "2024-06-21T00:50:36.100663Z", + "start_time": "2024-06-21T00:50:36.072748Z" + } + }, + "outputs": [], + "source": [ + "from oaklib import get_adapter\n", + "from oaklib.utilities.associations.edge_information_util import associations_to_matrix\n", + "\n", + "\n", + "ont_adapter = get_adapter(\"sqlite:obo:go\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "outputs": [], + "source": [ + "taxa = [\"9606\", \"6239\", \"7955\", \"3702\", \"559292\", \"4896\", \"7227\", \"10090\", ]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:28.056869Z", + "start_time": "2024-06-21T03:06:28.051930Z" + } + }, + "id": "5ff92fe5a9bcbbda" + }, + { + "cell_type": "code", + "execution_count": 48, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Taxon 9606 shape (44398, 22647)\n", + "Taxon 6239 shape (14675, 9794)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:pysolr:Unable to extract error message from invalid XML: syntax error: line 1, column 49\n", + "ERROR:pysolr:Solr responded with an error (HTTP 503): [Reason: None]\n", + "503 Service Unavailable

Service Unavailable

The server is temporarily unable to service yourrequest due to maintenance downtime or capacityproblems. Please try again later.

\n" + ] + }, + { + "ename": "SolrError", + "evalue": "Solr responded with an error (HTTP 503): [Reason: None]\n503 Service Unavailable

Service Unavailable

The server is temporarily unable to service yourrequest due to maintenance downtime or capacityproblems. Please try again later.

", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mSolrError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[48], line 4\u001B[0m\n\u001B[1;32m 2\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m tax \u001B[38;5;129;01min\u001B[39;00m taxa:\n\u001B[1;32m 3\u001B[0m assoc_adapter \u001B[38;5;241m=\u001B[39m get_adapter(\u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mamigo:NCBITaxon:\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mtax\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m\"\u001B[39m)\n\u001B[0;32m----> 4\u001B[0m assocs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mlist\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43massoc_adapter\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43massociations\u001B[49m\u001B[43m(\u001B[49m\u001B[43madd_closure_fields\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 5\u001B[0m matrix \u001B[38;5;241m=\u001B[39m associations_to_matrix(assocs)\n\u001B[1;32m 6\u001B[0m matrix_by_taxon[tax] \u001B[38;5;241m=\u001B[39m matrix\n", + "File \u001B[0;32m~/repos/ontology-access-kit/src/oaklib/implementations/amigo/amigo_implementation.py:253\u001B[0m, in \u001B[0;36mAmiGOImplementation.associations\u001B[0;34m(self, subjects, predicates, objects, property_filter, subject_closure_predicates, predicate_closure_predicates, object_closure_predicates, include_modified, add_closure_fields, **kwargs)\u001B[0m\n\u001B[1;32m 248\u001B[0m results \u001B[38;5;241m=\u001B[39m _query(solr, fq, select_fields)\n\u001B[1;32m 250\u001B[0m \u001B[38;5;66;03m# fq_list = [_fq_element(k, vs) for k, vs in fq.items()]\u001B[39;00m\n\u001B[1;32m 251\u001B[0m \u001B[38;5;66;03m# params = {\"fq\": fq_list, \"fl\": \",\".join(SELECT_FIELDS)}\u001B[39;00m\n\u001B[1;32m 252\u001B[0m \u001B[38;5;66;03m# results = solr.search(\"*:*\", rows=1000, **params)\u001B[39;00m\n\u001B[0;32m--> 253\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m doc \u001B[38;5;129;01min\u001B[39;00m results:\n\u001B[1;32m 254\u001B[0m assoc \u001B[38;5;241m=\u001B[39m Association(\n\u001B[1;32m 255\u001B[0m subject\u001B[38;5;241m=\u001B[39m_normalize(doc[BIOENTITY]),\n\u001B[1;32m 256\u001B[0m subject_label\u001B[38;5;241m=\u001B[39mdoc[BIOENTITY_LABEL],\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 262\u001B[0m aggregator_knowledge_source\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124minfores:go\u001B[39m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 263\u001B[0m )\n\u001B[1;32m 264\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m add_closure_fields:\n", + "File \u001B[0;32m~/repos/ontology-access-kit/src/oaklib/implementations/amigo/amigo_implementation.py:88\u001B[0m, in \u001B[0;36m_query\u001B[0;34m(solr, fq, fields, q, start, limit, **kwargs)\u001B[0m\n\u001B[1;32m 86\u001B[0m logging\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mQUERY: \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mq\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m PARAMS: \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mparams\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m 87\u001B[0m \u001B[38;5;28;01mwhile\u001B[39;00m \u001B[38;5;28;01mTrue\u001B[39;00m:\n\u001B[0;32m---> 88\u001B[0m results \u001B[38;5;241m=\u001B[39m \u001B[43msolr\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msearch\u001B[49m\u001B[43m(\u001B[49m\u001B[43mq\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mrows\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mlimit\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mstart\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mstart\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mparams\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 89\u001B[0m \u001B[38;5;28;01myield from\u001B[39;00m results\n\u001B[1;32m 90\u001B[0m logging\u001B[38;5;241m.\u001B[39mdebug(\u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mCHECKING: \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mstart\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m + \u001B[39m\u001B[38;5;132;01m{\u001B[39;00m\u001B[38;5;28mlen\u001B[39m(results)\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m >= \u001B[39m\u001B[38;5;132;01m{\u001B[39;00mresults\u001B[38;5;241m.\u001B[39mhits\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m\"\u001B[39m)\n", + "File \u001B[0;32m~/Library/Caches/pypoetry/virtualenvs/oaklib-OeQZizwE-py3.9/lib/python3.9/site-packages/pysolr.py:827\u001B[0m, in \u001B[0;36mSolr.search\u001B[0;34m(self, q, search_handler, **kwargs)\u001B[0m\n\u001B[1;32m 825\u001B[0m params \u001B[38;5;241m=\u001B[39m {\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mq\u001B[39m\u001B[38;5;124m\"\u001B[39m: q}\n\u001B[1;32m 826\u001B[0m params\u001B[38;5;241m.\u001B[39mupdate(kwargs)\n\u001B[0;32m--> 827\u001B[0m response \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_select\u001B[49m\u001B[43m(\u001B[49m\u001B[43mparams\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mhandler\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43msearch_handler\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 828\u001B[0m decoded \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdecoder\u001B[38;5;241m.\u001B[39mdecode(response)\n\u001B[1;32m 830\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mlog\u001B[38;5;241m.\u001B[39mdebug(\n\u001B[1;32m 831\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFound \u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m search results.\u001B[39m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 832\u001B[0m \u001B[38;5;66;03m# cover both cases: there is no response key or value is None\u001B[39;00m\n\u001B[1;32m 833\u001B[0m (decoded\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mresponse\u001B[39m\u001B[38;5;124m\"\u001B[39m, {}) \u001B[38;5;129;01mor\u001B[39;00m {})\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mnumFound\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;241m0\u001B[39m),\n\u001B[1;32m 834\u001B[0m )\n", + "File \u001B[0;32m~/Library/Caches/pypoetry/virtualenvs/oaklib-OeQZizwE-py3.9/lib/python3.9/site-packages/pysolr.py:488\u001B[0m, in \u001B[0;36mSolr._select\u001B[0;34m(self, params, handler)\u001B[0m\n\u001B[1;32m 485\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(params_encoded) \u001B[38;5;241m<\u001B[39m \u001B[38;5;241m1024\u001B[39m:\n\u001B[1;32m 486\u001B[0m \u001B[38;5;66;03m# Typical case.\u001B[39;00m\n\u001B[1;32m 487\u001B[0m path \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m/?\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;241m%\u001B[39m (handler, params_encoded)\n\u001B[0;32m--> 488\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_send_request\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mget\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mpath\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 489\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m 490\u001B[0m \u001B[38;5;66;03m# Handles very long queries by submitting as a POST.\u001B[39;00m\n\u001B[1;32m 491\u001B[0m path \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m/\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;241m%\u001B[39m handler\n", + "File \u001B[0;32m~/Library/Caches/pypoetry/virtualenvs/oaklib-OeQZizwE-py3.9/lib/python3.9/site-packages/pysolr.py:463\u001B[0m, in \u001B[0;36mSolr._send_request\u001B[0;34m(self, method, path, body, headers, files)\u001B[0m\n\u001B[1;32m 449\u001B[0m solr_message \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_extract_error(resp)\n\u001B[1;32m 450\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mlog\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 451\u001B[0m error_message,\n\u001B[1;32m 452\u001B[0m resp\u001B[38;5;241m.\u001B[39mstatus_code,\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 461\u001B[0m },\n\u001B[1;32m 462\u001B[0m )\n\u001B[0;32m--> 463\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m SolrError(error_message \u001B[38;5;241m%\u001B[39m (resp\u001B[38;5;241m.\u001B[39mstatus_code, solr_message))\n\u001B[1;32m 465\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m force_unicode(resp\u001B[38;5;241m.\u001B[39mcontent)\n", + "\u001B[0;31mSolrError\u001B[0m: Solr responded with an error (HTTP 503): [Reason: None]\n503 Service Unavailable

Service Unavailable

The server is temporarily unable to service yourrequest due to maintenance downtime or capacityproblems. Please try again later.

" + ] + } + ], + "source": [ + "matrix_by_taxon = {}\n", + "for tax in taxa:\n", + " assoc_adapter = get_adapter(f\"amigo:NCBITaxon:{tax}\")\n", + " assocs = list(assoc_adapter.associations(add_closure_fields=True))\n", + " matrix = associations_to_matrix(assocs)\n", + " matrix_by_taxon[tax] = matrix\n", + " print(f\"Taxon {tax} shape {matrix.arr.shape}\")" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:09:58.761418Z", + "start_time": "2024-06-21T03:06:28.801736Z" + } + }, + "id": "f0196639fef3e874" + }, + { + "cell_type": "code", + "execution_count": 17, + "outputs": [ + { + "data": { + "text/plain": "2" + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(matrix_by_taxon)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T01:04:14.529019Z", + "start_time": "2024-06-21T01:04:14.520402Z" + } + }, + "id": "f3d95aa29e00f78" + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "data": { + "text/plain": "132140" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T00:43:18.061005Z", + "start_time": "2024-06-21T00:43:18.054290Z" + } + }, + "id": "363d0d6676c2c39b" + }, + { + "cell_type": "code", + "execution_count": 6, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T00:43:19.149833Z", + "start_time": "2024-06-21T00:43:18.072717Z" + } + }, + "id": "b303c5da2f0dca38" + }, + { + "cell_type": "code", + "execution_count": 7, + "outputs": [], + "source": [ + "c=\"GO:0008527\"\n", + "p=\"GO:0050912\"\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T00:43:19.154373Z", + "start_time": "2024-06-21T00:43:19.150376Z" + } + }, + "id": "9a287e3fe19ea32c" + }, + { + "cell_type": "code", + "execution_count": 18, + "outputs": [], + "source": [ + "from oaklib.utilities.associations.edge_information_util import calculate_edge_information\n", + "\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T01:04:35.298149Z", + "start_time": "2024-06-21T01:04:35.291895Z" + } + }, + "id": "1905efe69fe136a3" + }, + { + "cell_type": "code", + "execution_count": 19, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7227 0.12928301694496636\n", + "10090 0.405992359675837\n" + ] + } + ], + "source": [ + "for t, matrix in matrix_by_taxon.items():\n", + " print(t, calculate_edge_information(c, p, matrix))" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T01:04:52.016589Z", + "start_time": "2024-06-21T01:04:51.494519Z" + } + }, + "id": "5bfcb4729b183682" + }, + { + "cell_type": "code", + "execution_count": 38, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'child': 'GO:0000943', 'parent': 'GO:0110165', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0001933', 'parent': 'GO:0006468', 'predicate': 'RO:0002212', '7227': 2.8187596853298533, '10090': 1.0951572330403403}\n", + "{'child': 'GO:0002503', 'parent': 'GO:0002495', 'predicate': 'BFO:0000050', '7227': None, '10090': 0.8073549220576037}\n", + "{'child': 'GO:0002869', 'parent': 'GO:0002904', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0003678', 'parent': 'GO:0032508', 'predicate': 'BFO:0000050', '7227': 0.22239242133644765, '10090': 0.32192809488736174}\n", + "{'child': 'GO:0004823', 'parent': 'GO:0004812', 'predicate': 'rdfs:subClassOf', '7227': 4.247927513443585, '10090': 4.357552004618084}\n", + "{'child': 'GO:0005743', 'parent': 'GO:0019866', 'predicate': 'rdfs:subClassOf', '7227': 0.05916207246814409, '10090': 0.09780478547179872}\n", + "{'child': 'GO:0006364', 'parent': 'GO:0042254', 'predicate': 'BFO:0000050', '7227': 0.5341133592254037, '10090': 0.5756846871331458}\n", + "{'child': 'GO:0006982', 'parent': 'GO:0033993', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 8.779719355143403}\n", + "{'child': 'GO:0007563', 'parent': 'GO:2000026', 'predicate': 'rdfs:subClassOf', '7227': 5.357552004618083, '10090': None}\n", + "{'child': 'GO:0008764', 'parent': 'GO:0016881', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0009398', 'parent': 'GO:0009156', 'predicate': 'rdfs:subClassOf', '7227': 4.321928094887362, '10090': 5.1292830169449655}\n", + "{'child': 'GO:0010006', 'parent': 'GO:0009707', 'predicate': 'BFO:0000050', '7227': None, '10090': None}\n", + "{'child': 'GO:0010560', 'parent': 'GO:0010559', 'predicate': 'rdfs:subClassOf', '7227': 1.0, '10090': 0.8744691179161403}\n", + "{'child': 'GO:0010986', 'parent': 'GO:0010984', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 1.938599455335856}\n", + "{'child': 'GO:0015310', 'parent': 'GO:0015078', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0015995', 'parent': 'GO:0006779', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0016906', 'parent': 'GO:0035251', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0018642', 'parent': 'GO:0016709', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0019356', 'parent': 'GO:0019357', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0019917', 'parent': 'GO:0019122', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0021946', 'parent': 'GO:0021535', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0030388', 'parent': 'GO:1901135', 'predicate': 'rdfs:subClassOf', '7227': 7.016808287686553, '10090': 6.602884408718419}\n", + "{'child': 'GO:0031025', 'parent': 'GO:0000923', 'predicate': 'RO:0002590', '7227': None, '10090': None}\n", + "{'child': 'GO:0031609', 'parent': 'GO:0031603', 'predicate': 'BFO:0000050', '7227': None, '10090': None}\n", + "{'child': 'GO:0032218', 'parent': 'GO:0051180', 'predicate': 'rdfs:subClassOf', '7227': 2.700439718141091, '10090': 3.1154772174199348}\n", + "{'child': 'GO:0032694', 'parent': 'GO:0032614', 'predicate': 'RO:0002212', '7227': None, '10090': None}\n", + "{'child': 'GO:0033118', 'parent': 'GO:0033117', 'predicate': 'RO:0002007', '7227': None, '10090': None}\n", + "{'child': 'GO:0033717', 'parent': 'GO:0008875', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0034346', 'parent': 'GO:0034343', 'predicate': 'RO:0002213', '7227': None, '10090': 0.0}\n", + "{'child': 'GO:0035025', 'parent': 'GO:0007266', 'predicate': 'RO:0002213', '7227': 0.4594316186372964, '10090': 0.8278190246173196}\n", + "{'child': 'GO:0035603', 'parent': 'GO:0030097', 'predicate': 'BFO:0000050', '7227': None, '10090': 9.696967526234285}\n", + "{'child': 'GO:0036237', 'parent': 'GO:0004553', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0039707', 'parent': 'GO:0016032', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0042571', 'parent': 'GO:0005615', 'predicate': 'BFO:0000050', '7227': None, '10090': 6.179198227699055}\n", + "{'child': 'GO:0043151', 'parent': 'GO:0000731', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0043673', 'parent': 'GO:0043668', 'predicate': 'BFO:0000050', '7227': None, '10090': None}\n", + "{'child': 'GO:0044542', 'parent': 'GO:0044541', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0045300', 'parent': 'GO:0016717', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0045831', 'parent': 'GO:0010461', 'predicate': 'RO:0002212', '7227': None, '10090': None}\n", + "{'child': 'GO:0046244', 'parent': 'GO:0009696', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0046761', 'parent': 'GO:0046753', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 0.12553088208385965}\n", + "{'child': 'GO:0047537', 'parent': 'GO:0008483', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0048303', 'parent': 'GO:0048302', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0048787', 'parent': 'GO:0042734', 'predicate': 'BFO:0000050', '7227': 5.0, '10090': 1.7241252483927818}\n", + "{'child': 'GO:0050625', 'parent': 'GO:0016655', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0051157', 'parent': 'GO:0019527', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0051709', 'parent': 'GO:0031640', 'predicate': 'RO:0002211', '7227': None, '10090': 2.9860608090421277}\n", + "{'child': 'GO:0052805', 'parent': 'GO:1901565', 'predicate': 'rdfs:subClassOf', '7227': 9.041659151637214, '10090': 7.54432051622381}\n", + "{'child': 'GO:0060295', 'parent': 'GO:0003352', 'predicate': 'rdfs:subClassOf', '7227': 1.8073549220576037, '10090': 0.4043902550793348}\n", + "{'child': 'GO:0060714', 'parent': 'GO:0048646', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0061197', 'parent': 'GO:0061196', 'predicate': 'BFO:0000050', '7227': None, '10090': 0.22239242133644765}\n", + "{'child': 'GO:0061724', 'parent': 'GO:0005811', 'predicate': 'RO:0002233', '7227': 2.700439718141091, '10090': 4.894817763307943}\n", + "{'child': 'GO:0070059', 'parent': 'GO:0034976', 'predicate': 'rdfs:subClassOf', '7227': 4.087462841250339, '10090': 2.47186872187552}\n", + "{'child': 'GO:0070620', 'parent': 'GO:0098797', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0071189', 'parent': 'GO:0071183', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0071651', 'parent': 'GO:0032722', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 3.857980995127571}\n", + "{'child': 'GO:0072185', 'parent': 'GO:0072075', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 3.3219280948873617}\n", + "{'child': 'GO:0075184', 'parent': 'GO:0050793', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0090033', 'parent': 'GO:0045927', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0090483', 'parent': 'GO:0030572', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0097400', 'parent': 'GO:0097398', 'predicate': 'BFO:0000050', '7227': None, '10090': 1.0641303374197157}\n", + "{'child': 'GO:0098736', 'parent': 'GO:0002026', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 4.954196310386875}\n", + "{'child': 'GO:0099568', 'parent': 'GO:0005737', 'predicate': 'rdfs:subClassOf', '7227': 4.972578498675761, '10090': 5.3494456155177526}\n", + "{'child': 'GO:0102914', 'parent': 'GO:0008168', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0110080', 'parent': 'GO:0110079', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:0140131', 'parent': 'GO:0048247', 'predicate': 'RO:0002213', '7227': None, '10090': 0.39592867633113826}\n", + "{'child': 'GO:0140813', 'parent': 'GO:0015747', 'predicate': 'BFO:0000050', '7227': None, '10090': None}\n", + "{'child': 'GO:1900017', 'parent': 'GO:0002534', 'predicate': 'RO:0002213', '7227': None, '10090': -1.6880559936852588}\n", + "{'child': 'GO:1900362', 'parent': 'GO:0051050', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:1900711', 'parent': 'GO:1900608', 'predicate': 'RO:0002212', '7227': None, '10090': None}\n", + "{'child': 'GO:1901035', 'parent': 'GO:2000486', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:1901448', 'parent': 'GO:1901422', 'predicate': 'RO:0002211', '7227': None, '10090': None}\n", + "{'child': 'GO:1901866', 'parent': 'GO:0016123', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:1902245', 'parent': 'GO:1902244', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:1902728', 'parent': 'GO:1902724', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 0.0}\n", + "{'child': 'GO:1903136', 'parent': 'GO:0005507', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 2.979822118062369}\n", + "{'child': 'GO:1903555', 'parent': 'GO:0071706', 'predicate': 'RO:0002211', '7227': None, '10090': -2.6147098441152075}\n", + "{'child': 'GO:1903949', 'parent': 'GO:0045760', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 4.0}\n", + "{'child': 'GO:1904333', 'parent': 'GO:2000573', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:1904735', 'parent': 'GO:0031998', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 4.523561956057012}\n", + "{'child': 'GO:1905135', 'parent': 'GO:0015878', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 0.5849625007211561}\n", + "{'child': 'GO:1905551', 'parent': 'GO:1903828', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 6.965784284662087}\n", + "{'child': 'GO:1905941', 'parent': 'GO:1905939', 'predicate': 'rdfs:subClassOf', '7227': 0.0, '10090': 0.5849625007211561}\n", + "{'child': 'GO:1990608', 'parent': 'GO:0044732', 'predicate': 'RO:0004009', '7227': None, '10090': None}\n", + "{'child': 'GO:2000156', 'parent': 'GO:0006890', 'predicate': 'RO:0002211', '7227': None, '10090': 4.426264754702098}\n", + "{'child': 'GO:2000509', 'parent': 'GO:0002689', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': 4.087462841250339}\n", + "{'child': 'GO:2000883', 'parent': 'GO:2000881', 'predicate': 'rdfs:subClassOf', '7227': None, '10090': None}\n", + "{'child': 'GO:2001268', 'parent': 'GO:2001234', 'predicate': 'rdfs:subClassOf', '7227': 4.6438561897747235, '10090': 5.011227255423254}\n" + ] + } + ], + "source": [ + "rows = []\n", + "for s, p, o in ont_adapter.relationships():\n", + " if not s.startswith(\"GO:\"):\n", + " continue\n", + " if not o.startswith(\"GO:\"):\n", + " continue\n", + " row = {\"child\": s, \"parent\": o, \"predicate\": p}\n", + " for t, matrix in matrix_by_taxon.items():\n", + " v = calculate_edge_information(s, o, matrix)\n", + " row[t] = v\n", + " rows.append(row)\n", + " if len(rows) % 1000 == 0:\n", + " print(row)\n", + " " + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:05:00.689216Z", + "start_time": "2024-06-21T03:03:58.650867Z" + } + }, + "id": "3234ab59d5764c9e" + }, + { + "cell_type": "code", + "execution_count": 39, + "outputs": [], + "source": [ + "import pandas as pd\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:05:00.698602Z", + "start_time": "2024-06-21T03:05:00.691144Z" + } + }, + "id": "b196c3c52b341b7f" + }, + { + "cell_type": "code", + "execution_count": 40, + "outputs": [], + "source": [ + "def has_val(row: dict):\n", + " for k, v in row.items():\n", + " if k not in [\"child\", \"parent\", \"predicate\"]:\n", + " if v is not None:\n", + " return True\n", + " return False" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:05:00.698869Z", + "start_time": "2024-06-21T03:05:00.693147Z" + } + }, + "id": "20222d40e7efd529" + }, + { + "cell_type": "code", + "execution_count": 41, + "outputs": [], + "source": [ + "filtered_rows = [r for r in rows if has_val(r)]" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:05:00.760725Z", + "start_time": "2024-06-21T03:05:00.709894Z" + } + }, + "id": "3587837f8196bfe4" + }, + { + "cell_type": "code", + "execution_count": 42, + "outputs": [], + "source": [ + "for row in filtered_rows:\n", + " row[\"child_label\"] = ont_adapter.label(row[\"child\"])\n", + " row[\"parent_label\"] = ont_adapter.label(row[\"parent\"])" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:01.475651Z", + "start_time": "2024-06-21T03:05:44.967917Z" + } + }, + "id": "d8210aebbcf8347a" + }, + { + "cell_type": "code", + "execution_count": 43, + "outputs": [ + { + "data": { + "text/plain": " child parent predicate 7227 10090 \\\n0 GO:0000001 GO:0005739 obo:GOREL_0002003 7.813781 NaN \n1 GO:0000001 GO:0048308 rdfs:subClassOf 0.000000 NaN \n2 GO:0000001 GO:0048311 rdfs:subClassOf 1.459432 NaN \n3 GO:0000002 GO:0007005 rdfs:subClassOf 4.650254 3.865499 \n4 GO:0000009 GO:0000030 rdfs:subClassOf 3.321928 3.643856 \n... ... ... ... ... ... \n49354 GO:2001306 GO:1901617 rdfs:subClassOf NaN 7.491853 \n49355 GO:2001306 GO:2001301 rdfs:subClassOf NaN 2.000000 \n49356 GO:2001306 GO:2001304 rdfs:subClassOf NaN 0.000000 \n49357 GO:2001311 GO:0006650 rdfs:subClassOf NaN 7.049849 \n49358 GO:2001311 GO:0052646 rdfs:subClassOf NaN 2.807355 \n\n child_label \\\n0 mitochondrion inheritance \n1 mitochondrion inheritance \n2 mitochondrion inheritance \n3 mitochondrial genome maintenance \n4 alpha-1,6-mannosyltransferase activity \n... ... \n49354 lipoxin B4 biosynthetic process \n49355 lipoxin B4 biosynthetic process \n49356 lipoxin B4 biosynthetic process \n49357 lysobisphosphatidic acid metabolic process \n49358 lysobisphosphatidic acid metabolic process \n\n parent_label \n0 mitochondrion \n1 organelle inheritance \n2 mitochondrion distribution \n3 mitochondrion organization \n4 mannosyltransferase activity \n... ... \n49354 organic hydroxy compound biosynthetic process \n49355 lipoxin biosynthetic process \n49356 lipoxin B4 metabolic process \n49357 glycerophospholipid metabolic process \n49358 alditol phosphate metabolic process \n\n[49359 rows x 7 columns]", + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
childparentpredicate722710090child_labelparent_label
0GO:0000001GO:0005739obo:GOREL_00020037.813781NaNmitochondrion inheritancemitochondrion
1GO:0000001GO:0048308rdfs:subClassOf0.000000NaNmitochondrion inheritanceorganelle inheritance
2GO:0000001GO:0048311rdfs:subClassOf1.459432NaNmitochondrion inheritancemitochondrion distribution
3GO:0000002GO:0007005rdfs:subClassOf4.6502543.865499mitochondrial genome maintenancemitochondrion organization
4GO:0000009GO:0000030rdfs:subClassOf3.3219283.643856alpha-1,6-mannosyltransferase activitymannosyltransferase activity
........................
49354GO:2001306GO:1901617rdfs:subClassOfNaN7.491853lipoxin B4 biosynthetic processorganic hydroxy compound biosynthetic process
49355GO:2001306GO:2001301rdfs:subClassOfNaN2.000000lipoxin B4 biosynthetic processlipoxin biosynthetic process
49356GO:2001306GO:2001304rdfs:subClassOfNaN0.000000lipoxin B4 biosynthetic processlipoxin B4 metabolic process
49357GO:2001311GO:0006650rdfs:subClassOfNaN7.049849lysobisphosphatidic acid metabolic processglycerophospholipid metabolic process
49358GO:2001311GO:0052646rdfs:subClassOfNaN2.807355lysobisphosphatidic acid metabolic processalditol phosphate metabolic process
\n

49359 rows × 7 columns

\n
" + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(filtered_rows)\n", + "df" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:01.540034Z", + "start_time": "2024-06-21T03:06:01.494862Z" + } + }, + "id": "ae6bae32526f09ad" + }, + { + "cell_type": "code", + "execution_count": 44, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mkdir: results: File exists\r\n" + ] + } + ], + "source": [ + "!mkdir results" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:01.723399Z", + "start_time": "2024-06-21T03:06:01.540567Z" + } + }, + "id": "fb27ed2f8067b8e0" + }, + { + "cell_type": "code", + "execution_count": 45, + "outputs": [], + "source": [ + "df.to_csv(\"results/edge_information.csv\", index=False)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:02.026013Z", + "start_time": "2024-06-21T03:06:01.730330Z" + } + }, + "id": "b3443f3e443af550" + }, + { + "cell_type": "code", + "execution_count": 46, + "outputs": [], + "source": [ + "old_matrix_by_taxon = matrix_by_taxon" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-06-21T03:06:16.113599Z", + "start_time": "2024-06-21T03:06:16.071054Z" + } + }, + "id": "33fc513d1090313a" + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "676e7d015135b3d0" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/poetry.lock b/poetry.lock index beaeca0ad..c19616474 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,12 +2,12 @@ [[package]] name = "adeft" -version = "0.11.2" +version = "0.12.3" description = "Acromine based Disambiguation of Entities From Text" optional = true -python-versions = "*" +python-versions = ">=3.7" files = [ - {file = "adeft-0.11.2.tar.gz", hash = "sha256:bf9b239d7989217b7d673eaf46ac2e8c1bfc97a0aac9a75cc2231e07438fc0a5"}, + {file = "adeft-0.12.3.tar.gz", hash = "sha256:3106eb30e5a655caf67db8433b265afa3f292e99bcdf76a720d0c180d2d4b8bb"}, ] [package.dependencies] @@ -15,7 +15,7 @@ appdirs = "*" boto3 = "*" flask = "*" nltk = "*" -scikit-learn = ">=0.20.0" +scikit-learn = ">=1.0" [package.extras] test = ["pytest", "pytest-cov"] @@ -172,13 +172,13 @@ dev = ["black", "coverage", "isort", "pre-commit", "pyenchant", "pylint"] [[package]] name = "annotated-types" -version = "0.6.0" +version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" files = [ - {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"}, - {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"}, + {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, + {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] [[package]] @@ -193,13 +193,13 @@ files = [ [[package]] name = "anyio" -version = "4.3.0" +version = "4.4.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.8" files = [ - {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"}, - {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"}, + {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"}, + {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"}, ] [package.dependencies] @@ -389,13 +389,13 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"] [[package]] name = "bcp47" -version = "0.0.4" +version = "0.1.0" description = "Language tags made easy" optional = false python-versions = "*" files = [ - {file = "bcp47-0.0.4-py3-none-any.whl", hash = "sha256:309d3bbaef8d6c9ac59d37ba2167cc6620b4e7467ec8f1e09641b659bb1c0c6d"}, - {file = "bcp47-0.0.4.tar.gz", hash = "sha256:4878d2f3e697ef39ef3891a147280705e4377d5a8d7eb0702129b8d4a3718702"}, + {file = "bcp47-0.1.0-py3-none-any.whl", hash = "sha256:a567b7fe881c900916a9db62ac8f792370c7ddf2664e601b74eeed35d8758aa5"}, + {file = 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prefixmaps = ">=0.1.2" ols-client = ">=0.1.1" airium = ">=0.2.5" -ndex2 = "^3.5.0" +ndex2 = ">=3.5.0" pysolr = "^3.9.0" eutils = ">=0.6.0" requests-cache = "^1.0.1" click = "*" urllib3 = {version = "< 2", optional = true} pydantic = "*" -jsonlines = "^4.0.0" -tenacity = "^8.2.3" -defusedxml = "^0.7.1" +jsonlines = "*" +tenacity = ">=8.2.3" +defusedxml = ">=0.7.1" [tool.poetry.dev-dependencies] diff --git a/src/oaklib/cli.py b/src/oaklib/cli.py index 1192461ed..7cd8c42fd 100644 --- a/src/oaklib/cli.py +++ b/src/oaklib/cli.py @@ -2744,21 +2744,28 @@ def information_content( writer.file = output if not isinstance(impl, SemanticSimilarityInterface): raise NotImplementedError(f"Cannot execute this with {type(impl)}") - if len(terms) == 0: - raise ValueError("You must specify a list of terms. Use '.all' for all terms") actual_predicates = _process_predicates_arg(predicates) n = 0 logging.info("Fetching ICs...") - for curie_it in chunk(query_terms_iterator(terms, impl)): - logging.info("** Next chunk:") - n += 1 + if terms: + for curie_it in chunk(query_terms_iterator(terms, impl)): + logging.info("** Next chunk:") + for curie, ic in impl.information_content_scores( + curie_it, + object_closure_predicates=actual_predicates, + use_associations=use_associations, + ): + obj = dict(id=curie, information_content=ic) + writer.emit(obj) + n += 1 + else: for curie, ic in impl.information_content_scores( - curie_it, - object_closure_predicates=actual_predicates, - use_associations=use_associations, + object_closure_predicates=actual_predicates, + use_associations=use_associations, ): obj = dict(id=curie, information_content=ic) writer.emit(obj) + n += 1 if n == 0: raise ValueError(f"No results for input: {terms}") writer.finish() @@ -6572,9 +6579,15 @@ def generate_lexical_replacements( "--patch-format", help="Output syntax for patches.", ) +@click.option( + "--exclude-defined/--no-exclude-defined", + default=False, + show_default=True, + help="Exclude terms that already have definitions", +) @output_option @output_type_option -def generate_definitions(terms, apply_patch, patch, patch_format, output, output_type, **kwargs): +def generate_definitions(terms, apply_patch, patch, patch_format, output, output_type, exclude_defined, **kwargs): """ Generate definitions for a term or terms. @@ -6606,8 +6619,14 @@ def generate_definitions(terms, apply_patch, patch, patch_format, output, output writer.output = output if not isinstance(impl, OntologyGenerationInterface): raise NotImplementedError - all_terms = query_terms_iterator(terms, impl) - curie_defns = impl.generate_definitions(list(all_terms), **kwargs) + all_terms = list(query_terms_iterator(terms, impl)) + logging.info(f"Generating definitions for {len(all_terms)} terms") + if exclude_defined: + exclusion_list = [x[0] for x in impl.definitions(all_terms)] + logging.info(f"Excluding {len(exclusion_list)} terms that already have definitions") + all_terms = list(set(all_terms) - set(exclusion_list)) + logging.info(f"Generating definitions for final list of {len(all_terms)} terms") + curie_defns = impl.generate_definitions(all_terms, **kwargs) change_list = [] for curie, defn in curie_defns: change = kgcl.NewTextDefinition( diff --git a/src/oaklib/implementations/agrkb/agrkb_implementation.py b/src/oaklib/implementations/agrkb/agrkb_implementation.py index bea04ea35..3277bb10b 100644 --- a/src/oaklib/implementations/agrkb/agrkb_implementation.py +++ b/src/oaklib/implementations/agrkb/agrkb_implementation.py @@ -122,15 +122,25 @@ def ontologies(self) -> Iterable[CURIE]: def node( self, curie: CURIE, strict=False, include_metadata=False, expand_curies=False ) -> obograph.Node: + """ + Get a node by CURIE. + + Currently the only node type supported is a gene. + + :param curie: + :param strict: + :param include_metadata: + :param expand_curies: + :return: + """ + session = self.requests_session() - url = f"{BASE_URL}/gene/{curie }" + url = f"{BASE_URL}/gene/{curie}" response = session.get(url) if response.status_code == 500 and not strict: return obograph.Node(id=curie) if response.status_code != 200: - raise ValueError( - f"Error fetching issues: {response.status_code} from {url} // {response.text}" - ) + return obograph.Node(id=curie) obj = response.json() meta = obograph.Meta() defn = obj.get("geneSynopsis", None) diff --git a/src/oaklib/implementations/amigo/amigo_implementation.py b/src/oaklib/implementations/amigo/amigo_implementation.py index 04bc65ee6..a37b9dfcf 100644 --- a/src/oaklib/implementations/amigo/amigo_implementation.py +++ b/src/oaklib/implementations/amigo/amigo_implementation.py @@ -2,6 +2,7 @@ import json import logging +import math from dataclasses import dataclass from time import sleep from typing import Any, Dict, Iterable, Iterator, List, Optional, Tuple @@ -21,6 +22,7 @@ ] from oaklib.interfaces.basic_ontology_interface import LANGUAGE_TAG, RELATIONSHIP +from oaklib.interfaces.semsim_interface import SemanticSimilarityInterface from oaklib.interfaces.usages_interface import UsagesInterface from oaklib.types import CURIE, PRED_CURIE, SUBSET_CURIE from oaklib.utilities.iterator_utils import chunk @@ -32,6 +34,7 @@ LIMIT = 10000 ONTOLOGY_CLASS_CATEGORY = "ontology_class" +BIOENTITY_CATEGORY = "ontology_class" # TODO: derive from schema DOCUMENT_CATEGORY = "document_category" @@ -132,6 +135,7 @@ class AmiGOImplementation( AssociationProviderInterface, SearchInterface, UsagesInterface, + SemanticSimilarityInterface, ): """ Wraps AmiGO endpoint. @@ -260,8 +264,8 @@ def associations( aggregator_knowledge_source="infores:go", ) if add_closure_fields: - assoc.subject_closure = doc[ISA_PARTOF_CLOSURE] - assoc.subject_closure_label = doc[ISA_PARTOF_CLOSURE_LABEL] + assoc.object_closure = doc[ISA_PARTOF_CLOSURE] + assoc.object_closure_label = doc[ISA_PARTOF_CLOSURE_LABEL] yield assoc def _association_query( @@ -274,9 +278,10 @@ def _association_query( predicate_closure_predicates: Optional[List[PRED_CURIE]] = None, object_closure_predicates: Optional[List[PRED_CURIE]] = None, include_modified: bool = False, + document_category: str = "annotation", **kwargs, ) -> Dict[str, Any]: - fq = {DOCUMENT_CATEGORY: ["annotation"]} + fq = {DOCUMENT_CATEGORY: [document_category]} if subjects: subjects = [_unnnormalize(s) for s in subjects] fq[BIOENTITY] = subjects @@ -311,7 +316,6 @@ def association_counts( >>> adapter = get_adapter("amigo:NCBITaxon:9606") >>> for term, count in adapter.association_counts(group_by="object"): ... print(f"Term: {term} Approx Count: {int(count / 1000) * 1000)}") - xxx :param subjects: :param predicates: @@ -456,3 +460,45 @@ def basic_search( for doc in results: yield doc["entity"] + + + def information_content_scores( + self, + curies: Optional[Iterable[CURIE]] = None, + predicates: List[PRED_CURIE] = None, + object_closure_predicates: List[PRED_CURIE] = None, + use_associations: bool = None, + term_to_entities_map: Dict[CURIE, List[CURIE]] = None, + **kwargs, + ) -> Iterator[Tuple[CURIE, float]]: + if curies and not isinstance(curies, list): + curies = list(curies) + fq = self._association_query( + predicates=predicates, + object_closure_predicates=object_closure_predicates, + # objects=curies, + document_category="bioentity", + ) + solr = self._solr + n_bioentities = None + for term, count in _faceted_query( + solr, fq, facet_field=DOCUMENT_CATEGORY, rows=0, facet_limit=-1, min_facet_count=1, **kwargs, + ): + if term == "bioentity": + n_bioentities = count + if n_bioentities is None: + raise ValueError("No bioentities found") + kwargs = {} + #if curies: + # kwargs["facet.query"] = [_fq_element(ISA_PARTOF_CLOSURE, curie) for curie in curies] + n = 0 + for term, count in _faceted_query( + solr, fq, facet_field=ISA_PARTOF_CLOSURE, rows=0, facet_limit=-1, min_facet_count=1, **kwargs, + ): + n += 1 + if curies and term not in curies: + continue + ic = - math.log(count / n_bioentities) / math.log(2) + yield term, ic + + logger.info(f"Iterated {n} counts") diff --git a/src/oaklib/implementations/llm_implementation.py b/src/oaklib/implementations/llm_implementation.py index b913f49a1..9a52df714 100644 --- a/src/oaklib/implementations/llm_implementation.py +++ b/src/oaklib/implementations/llm_implementation.py @@ -31,7 +31,7 @@ SeverityOptions, ValidationConfiguration, ) -from oaklib.datamodels.vocabulary import HAS_DBXREF, HAS_DEFINITION_CURIE, SKOS_EXACT_MATCH +from oaklib.datamodels.vocabulary import HAS_DBXREF, HAS_DEFINITION_CURIE, SKOS_EXACT_MATCH, IS_A from oaklib.interfaces import ( MappingProviderInterface, OboGraphInterface, @@ -187,7 +187,7 @@ class LLMImplementation( model: "llm.Model" = None """The LLM model to use.""" - default_model_id: str = "gpt-4-turbo" + default_model_id: str = "gpt-4o" allow_direct_grounding: bool = False """The point of this implementation is to perform NER and delegate to a grounded.""" @@ -241,6 +241,9 @@ def basic_search(self, *args, **kwargs) -> Iterator[CURIE]: def label(self, *args, **kwargs) -> Optional[str]: return self.wrapped_adapter.label(*args, **kwargs) + def definitions(self, *args, **kwargs): + yield from self.wrapped_adapter.definitions(*args, **kwargs) + def descendants( self, *args, @@ -408,14 +411,20 @@ def generate_definitions( model = self.get_model() if not isinstance(wrapped_adapter, OboGraphInterface): raise NotImplementedError("LLM can only suggest definitions for OBO graphs") - if style_hints is None: - style_hints = "" for curie in curies: node = wrapped_adapter.node(curie) info = f"id: {curie}\n" info += f"label: {node.lbl}\n" + for _, p, o in wrapped_adapter.relationships(curie): + p_label = "is_a" if p == IS_A else wrapped_adapter.label(p) + o_label = wrapped_adapter.label(o) + if p_label and o_label: + info += f"{p_label}: {o_label}\n" system_prompt = "Provide a textual definition for the given term." - system_prompt += style_hints + if style_hints: + system_prompt += " " + style_hints + logger.debug(f"System: {system_prompt}") + logger.debug(f"Prompt: {info}") response = model.prompt(info, system=system_prompt).text() yield curie, DefinitionPropertyValue(val=response) diff --git a/src/oaklib/implementations/quickgo/quickgo_implementation.py b/src/oaklib/implementations/quickgo/quickgo_implementation.py index 438db56ab..553277018 100644 --- a/src/oaklib/implementations/quickgo/quickgo_implementation.py +++ b/src/oaklib/implementations/quickgo/quickgo_implementation.py @@ -153,6 +153,8 @@ def node( return node def label(self, curie: CURIE, lang: Optional[LANGUAGE_TAG] = None) -> Optional[str]: + if curie.startswith("biolink:"): + return None try: node = self.node(curie) if node: diff --git a/src/oaklib/implementations/sqldb/sql_implementation.py b/src/oaklib/implementations/sqldb/sql_implementation.py index ba511b644..acdaa9dfd 100644 --- a/src/oaklib/implementations/sqldb/sql_implementation.py +++ b/src/oaklib/implementations/sqldb/sql_implementation.py @@ -324,7 +324,7 @@ class SqlImplementation( _information_content_cache: Dict[Tuple, float] = None _relationships_by_subject_index: Dict[CURIE, List[RELATIONSHIP]] = None - max_items_for_in_clause: int = field(default_factory=lambda: 1000) + max_items_for_in_clause: int = field(default_factory=lambda: 100) can_store_associations: bool = False """True if the underlying sqlite database has term_association populated.""" diff --git a/src/oaklib/interfaces/basic_ontology_interface.py b/src/oaklib/interfaces/basic_ontology_interface.py index 5f3070b9b..fe8b9fabf 100644 --- a/src/oaklib/interfaces/basic_ontology_interface.py +++ b/src/oaklib/interfaces/basic_ontology_interface.py @@ -1330,7 +1330,7 @@ def definitions( :param include_metadata: if true, include metadata :param include_missing: if true, include curies with no definition :param lang: language tag - :return: iterator over definition objects + :return: iterator over (id, definition, metadata) tuples """ if include_metadata: raise NotImplementedError() diff --git a/src/oaklib/interfaces/semsim_interface.py b/src/oaklib/interfaces/semsim_interface.py index 269c998e4..c3e52abe3 100644 --- a/src/oaklib/interfaces/semsim_interface.py +++ b/src/oaklib/interfaces/semsim_interface.py @@ -17,6 +17,7 @@ from oaklib.interfaces.basic_ontology_interface import BasicOntologyInterface from oaklib.interfaces.obograph_interface import OboGraphInterface from oaklib.types import CURIE, PRED_CURIE +from oaklib.utilities.iterator_utils import chunk from oaklib.utilities.obograph_utils import as_digraph from oaklib.utilities.semsim.similarity_utils import setwise_jaccard_similarity @@ -193,7 +194,7 @@ def get_information_content( def information_content_scores( self, - curies: Iterable[CURIE], + curies: Optional[Iterable[CURIE]] = None, predicates: List[PRED_CURIE] = None, object_closure_predicates: List[PRED_CURIE] = None, use_associations: bool = None, @@ -220,6 +221,17 @@ def information_content_scores( :param kwargs: :return: """ + if curies is None: + for curie_it in chunk(self.entities()): + yield from self.information_content_scores( + curie_it, + predicates=predicates, + object_closure_predicates=object_closure_predicates, + use_associations=use_associations, + term_to_entities_map=term_to_entities_map, + **kwargs, + ) + return curies = list(curies) if self.cached_information_content_map is None and use_associations: logging.info("Calculating and caching IC map from associations") diff --git a/src/oaklib/query.py b/src/oaklib/query.py index a3303ca97..8506566d0 100644 --- a/src/oaklib/query.py +++ b/src/oaklib/query.py @@ -606,6 +606,18 @@ def chain_results(v): subset = query_terms[0] query_terms = query_terms[1:] chain_results(adapter.subset_members(subset)) + elif term.startswith(".root"): + logging.debug(f"Roots: {term}") + params = _parse_params(term) + this_predicates = params.get("predicates", predicates) + roots = adapter.roots(predicates=this_predicates) + chain_results(roots) + elif term.startswith(".leaf"): + logging.debug(f"Leafs: {term}") + params = _parse_params(term) + this_predicates = params.get("predicates", predicates) + leafs = adapter.leafs(predicates=this_predicates) + chain_results(leafs) elif term.startswith(".is_obsolete"): logging.debug("Obsolete") chain_results(adapter.obsoletes()) @@ -766,6 +778,9 @@ def curies_from_file( if allow_labels and not adapter: raise ValueError("Must provide an adapter to resolve labels") for line in file.readlines(): + line = line.strip() + if not line: + continue line_no += 1 if ":" in line or not allow_labels: m = re.match(r"^(\S+)", line) diff --git a/src/oaklib/utilities/associations/edge_information_util.py b/src/oaklib/utilities/associations/edge_information_util.py new file mode 100644 index 000000000..52ee71395 --- /dev/null +++ b/src/oaklib/utilities/associations/edge_information_util.py @@ -0,0 +1,154 @@ +from dataclasses import dataclass +from math import floor +from typing import List, Tuple, Dict, Optional + +import click +import numpy as np + +from oaklib import BasicOntologyInterface, get_adapter +from oaklib.datamodels.association import Association +from oaklib.interfaces.association_provider_interface import AssociationProviderInterface +from oaklib.io.streaming_csv_writer import StreamingCsvWriter +from oaklib.types import CURIE + + +@dataclass +class MatrixData: + arr: np.ndarray + subject_index: Dict[CURIE, int] + object_index: Dict[CURIE, int] + subject_index_rev: Optional[Dict[int, CURIE]] = None + object_index_rev: Optional[Dict[int, CURIE]] = None + + def lookup_subject(self, subject: CURIE) -> List[int]: + """ + Look up a row in the matrix. + + :param subject: + :return: + """ + subject_ix = self.subject_index.get(subject) + if subject_ix is None: + return [] + row = self.arr[subject_ix, :] + return np.where(row > 0)[0].tolist() + + def lookup_object(self, object: CURIE) -> List[int]: + """ + Look up a column in the matrix. + + :param object: + :return: + """ + object_ix = self.object_index.get(object) + if object_ix is None: + return [] + column = self.arr[:, object_ix] + return np.where(column > 0)[0].tolist() + + def object_ic(self, object: CURIE) -> Optional[float]: + """ + Calculate the information content of an object. + + IC is log2 of the frequency of the object. + + :param object: + :return: + """ + object_ix = self.object_index.get(object) + if object_ix is None: + return None + column = self.arr[:, object_ix] + freq = np.sum(column) / self.arr.shape[0] + return -np.log2(freq) + + +def associations_to_matrix(associations: List[Association]) -> MatrixData: + """ + Convert a list of associations to a matrix. + + >>> from oaklib.datamodels.association import Association + >>> assoc_pairs = [("G1", ["E1", "E2"]), ("G2", ["E2", "E3"])] + >>> associations = [Association(subject=subject, object_closure=object_closure) for subject, object_closure in assoc_pairs] + >>> md = associations_to_matrix(associations) + >>> md.arr.shape + (2, 3) + >>> sorted([md.object_index_rev[i] for i in md.lookup_subject("G1")]) + ['E1', 'E2'] + >>> sorted([md.object_index_rev[i] for i in md.lookup_subject("G2")]) + ['E2', 'E3'] + >>> md.object_ic("E1") + 1.0 + >>> floor(md.object_ic("E2")) + 0 + >>> md.object_ic("E3") + 1.0 + >>> assert md.object_ic("E_MADE_UP") is None + + :param associations: + :param adapter: + :param entities_by_term: + :return: + """ + subjects = set() + objects = set() + for association in associations: + subjects.add(association.subject) + objects.update(association.object_closure) + matrix = np.zeros((len(subjects), len(objects))) + subject_ix = {term: index for index, term in enumerate(subjects)} + object_ix = {term: index for index, term in enumerate(objects)} + subject_ix_rev = {index: term for term, index in subject_ix.items()} + object_ix_rev = {index: term for term, index in object_ix.items()} + for association in associations: + subject = association.subject + for object in association.object_closure: + matrix[subject_ix[subject], object_ix[object]] = 1 + md = MatrixData(arr=matrix, subject_index=subject_ix, object_index=object_ix) + md.subject_index_rev = subject_ix_rev + md.object_index_rev = object_ix_rev + return md + + +def calculate_edge_information(child_term: CURIE, parent_term: CURIE, matrix: MatrixData) -> Optional[float]: + """ + Calculate edge information. + + :param adapter: + :param subject: + :param object: + :param entities_by_term: + :return: + """ + child_ic = matrix.object_ic(child_term) + parent_ic = matrix.object_ic(parent_term) + return child_ic - parent_ic if child_ic is not None and parent_ic is not None else None + + +# make this a click command +@click.command() +@click.option("--ont-adapter-handle", help="The ontology adapter handle.") +@click.option("--assoc-adapter-handle", help="The association adapter handle.") +def calculate_all(ont_adapter_handle: str, assoc_adapter_handle: str): + """ + Calculate all the edge information. + + :param ont_adapter_handle: + :param assoc_adapter_handle: + :return: + """ + ont_adapter = get_adapter(ont_adapter_handle) + assoc_adapter = get_adapter(assoc_adapter_handle) + if not isinstance(ont_adapter, BasicOntologyInterface): + raise ValueError("Ontology adapter must be a BasicOntologyInterface.") + if not isinstance(assoc_adapter, AssociationProviderInterface): + raise ValueError("Association adapter must be an AssociationProviderInterface.") + assocs = list(assoc_adapter.associations()) + matrix = associations_to_matrix(assocs) + writer = StreamingCsvWriter(ontology_interface=ont_adapter) + for s, p, o in ont_adapter.relationships(): + edge_info = calculate_edge_information(s, o, matrix) + if edge_info is not None: + writer.emit({"subject": s, "predicate": p, "object": o, "edge_information": edge_info}, + label_fields=["subject", "object"]) + return ont_adapter, matrix \ No newline at end of file diff --git a/src/oaklib/utilities/graph/relationship_walker.py b/src/oaklib/utilities/graph/relationship_walker.py index 36472302d..3b59050ce 100644 --- a/src/oaklib/utilities/graph/relationship_walker.py +++ b/src/oaklib/utilities/graph/relationship_walker.py @@ -48,8 +48,10 @@ def walk_up( ) next_curie = next_curies.pop() if not next_curie: - raise ValueError(f"Got an empty curie in list: {start_curies}") + raise ValueError(f"Got an empty curie; start: {start_curies}") for _, pred, filler in oi.relationships([next_curie], predicates, **kwargs): + if not filler: + raise ValueError(f"Got an empty filler; curie: {next_curie} p={pred}") if filler not in visited: next_curies.append(filler) visited.append(filler)