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May 12, 2017 14:30
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"ChEBI / 2016\n", | |
"Number of completely invalid molecular formulae (not corresponding to ANY molecule): 1700\n", | |
"Number of molecular formulae we can fix without re-processing (at least one molecule in the database): 1077\n", | |
"Number of molecular formulae that need to be fixed (at least one 'molecule' is in fact a group): 2777\n", | |
"HMDB / 2016\n", | |
"Number of completely invalid molecular formulae (not corresponding to ANY molecule): 0\n", | |
"Number of molecular formulae we can fix without re-processing (at least one molecule in the database): 0\n", | |
"Number of molecular formulae that need to be fixed (at least one 'molecule' is in fact a group): 0\n", | |
"LIPID_MAPS / 2016\n", | |
"Number of completely invalid molecular formulae (not corresponding to ANY molecule): 1\n", | |
"Number of molecular formulae we can fix without re-processing (at least one molecule in the database): 0\n", | |
"Number of molecular formulae that need to be fixed (at least one 'molecule' is in fact a group): 1\n", | |
"SwissLipids / 2016\n", | |
"Number of completely invalid molecular formulae (not corresponding to ANY molecule): 0\n", | |
"Number of molecular formulae we can fix without re-processing (at least one molecule in the database): 0\n", | |
"Number of molecular formulae that need to be fixed (at least one 'molecule' is in fact a group): 0\n" | |
] | |
} | |
], | |
"source": [ | |
"import requests\n", | |
"\n", | |
"server = 'http://annotate.metasp.eu:5000/v1/'\n", | |
"\n", | |
"wtf = {}\n", | |
"\n", | |
"for db in requests.get(server + 'databases').json()['data']:\n", | |
" dbId = db['id']\n", | |
" print('{} / {}'.format(db['name'], db['version']))\n", | |
" molecules = requests.get(server + 'databases/{}/molecules?limit=1000000'.format(dbId)).json()['data']\n", | |
" \n", | |
" failures = [m for m in molecules if not m['inchi'].startswith('InChI')]\n", | |
" failure_mf = {m['sf'] for m in failures}\n", | |
" all_mf = {m['sf'] for m in molecules}\n", | |
" valid_mf = {m['sf'] for m in molecules if m['inchi'].startswith('InChI')}\n", | |
" \n", | |
" wtf[dbId] = all_mf.difference(valid_mf)\n", | |
"\n", | |
" print(\"Number of completely invalid molecular formulae (not corresponding to ANY molecule):\", len(all_mf.difference(valid_mf)))\n", | |
" print(\"Number of molecular formulae we can fix without re-processing (at least one molecule in the database):\", len(valid_mf.intersection(failure_mf)))\n", | |
" print(\"Number of molecular formulae that need to be fixed (at least one 'molecule' is in fact a group):\", len(failure_mf))" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"1700" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"len(wtf[2])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"#!pip install git+https://github.com/metaspace2020/[email protected] -U" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from sm_annotation_utils import sm_annotation_utils\n", | |
"sm = sm_annotation_utils.SMInstance()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"chebi_annot = sm._gqclient.getAnnotations({'database': 'ChEBI'})" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 18, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"384280" | |
] | |
}, | |
"execution_count": 18, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"len(chebi_annot)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 19, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [ | |
"import pandas as pd" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 26, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"df = pd.DataFrame.from_records(\n", | |
" [{\n", | |
" 'mf': a['sumFormula'], \n", | |
" 'adduct': a['adduct'], \n", | |
" 'ds': a['dataset']['name'], \n", | |
" 'msm': a['msmScore'],\n", | |
" 'fdr': a['fdrLevel']\n", | |
" } for a in chebi_annot if a is not None]\n", | |
")" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 31, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"@ FDR = 0.05\n", | |
"total annotations: 12920\n", | |
"non-molecular annotations: 1359 (10.5%)\n", | |
"@ FDR = 0.1\n", | |
"total annotations: 44885\n", | |
"non-molecular annotations: 6406 (14.3%)\n", | |
"@ FDR = 0.2\n", | |
"total annotations: 116102\n", | |
"non-molecular annotations: 15139 (13.0%)\n", | |
"@ FDR = 0.5\n", | |
"total annotations: 384245\n", | |
"non-molecular annotations: 38799 (10.1%)\n" | |
] | |
} | |
], | |
"source": [ | |
"for cutoff in [0.05, 0.1, 0.2, 0.5]:\n", | |
" print(\"@ FDR =\", cutoff)\n", | |
" subdf = df[df['fdr'] <= cutoff]\n", | |
" total = len(subdf)\n", | |
" print(\"total annotations:\", len(subdf))\n", | |
" nonmol = subdf['mf'].isin(wtf[2]).sum()\n", | |
" print(\"non-molecular annotations:\", nonmol, '({:.1f}%)'.format(nonmol / total * 100))" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.5.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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