def testMain(self):
sql = writeToSQL()
hmdb = hmdbData()
hmdb.getDatabaseFiles()
idconvert = IDconversion()
stat = getStatistics()
wiki = wikipathwaysData()
react = reactomeData()
kegg = KeggData()
print('Running overlap plot test case...')
hmdb.getGenes()
hmdb.getPathwaysLinkedToGene()
wiki.getEverything()
wiki.getCommonNameForChebi()
react.getGenes()
react.getCommonNameFromUniprot()
kegg.getPathways()
kegg.getMetabolites()
kegg.getGenes()
kegg.getGeneInfo()
kegg.getPathwayLinkedToGene()
#idconvert.GeneConvert(hmdb.geneInfoDictionary, "hmdb")
hmdbgenenum = sql.createRampGeneID(hmdb.geneInfoDictionary, "hmdb", 0)
keggnum = sql.createRampGeneID(kegg.geneInfoDictionary, 'kegg',
hmdbgenenum)
wikinum = sql.createRampGeneID(wiki.geneInfoDictionary, 'wiki',
keggnum)
reactnum = sql.createRampGeneID(react.geneInfoDictionary, 'reactome',
wikinum)
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, 'Gene')
def testMain(self):
kegg = KeggData()
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
# get database file
kegg.getDatabaseFiles()
print('get pathways')
kegg.getPathways()
kegg.getPathways_with_genes()
print(len(kegg.pathwayDictionary))
print('get metabolites')
kegg.getMetabolites()
print('get synonyms and chebi')
kegg.getSynonymsAndCHEBI()
print(len(kegg.metaboliteIDDictionary))
print(kegg.metaboliteIDDictionary["C00002"])
print(kegg.metaboliteIDDictionary["C00001"])
print('get genes')
kegg.getGenes()
print(len(kegg.geneInfoDictionary))
kegg.getGeneInfo()
kegg.getPathwayLinkedToGene()
kegg.write_myself_files(database='kegg')
idconvert.GeneConvert(kegg.geneInfoDictionary, "kegg")
# Check duplicates
kegg.write_myself_files('kegg')
keggcompoundnum = sql.createRampCompoundID(kegg.metaboliteIDDictionary,
"kegg", 0)
kegggenenum = sql.createRampGeneID(kegg.geneInfoDictionary, "kegg", 0)
keggnumbers = sql.write(
kegg.metaboliteCommonName, kegg.pathwayDictionary,
kegg.pathwayCategory, kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary, kegg.pathwaysWithGenesDictionary,
kegg.metabolitesLinkedToGenes, kegg.geneInfoDictionary,
kegg.biofluidLocation, kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology, kegg.exoEndoDictionary,
kegg.exoEndo, kegg.tissueLocation, kegg.tissue, "kegg", 0, 0)
print('metaboliteIDdict number is ' +
str(len(kegg.metaboliteIDDictionary)))
print('GeneInfo number is ' + str(len(kegg.geneInfoDictionary)))
print('PathwayDict number is ' + str(len(kegg.pathwayDictionary)))
print('MetabolitesWithPath is ' +
str(len(kegg.metabolitesWithPathwaysDictionary)))
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
def testMain(self):
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
wikipathways = wikipathwaysData()
wikipathways.getDatabaseFiles()
wikipathways.getEverything()
print(wikipathways.setOfType)
wikipathways.getCommonNameForChebi()
idconvert.GeneConvert(wikipathways.geneInfoDictionary, "wiki")
sql.checkForWithinDatabaseDuplicatesCompound(
wikipathways.metaboliteIDDictionary, "wiki")
sql.checkForWithinDatabaseDuplicatesGene(
wikipathways.geneInfoDictionary, "wiki")
wikicompoundnum = sql.createRampCompoundID(
wikipathways.metaboliteIDDictionary, "wiki", 0)
wikigenenum = sql.createRampGeneID(wikipathways.geneInfoDictionary,
"wiki", 0)
print("Write to file...")
wikipathwaysnumbers = sql.write(
wikipathways.metaboliteCommonName, wikipathways.pathwayDictionary,
wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.metabolitesLinkedToGenes,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, wikipathways.exoEndo,
wikipathways.tissueLocation, wikipathways.tissue, "wiki", 0, 0)
print("Pathways number is " + str(len(wikipathways.pathwayDictionary)))
print("metabolites number is " +
str(len(wikipathways.metaboliteIDDictionary)))
print('genes number is ' + str(len(wikipathways.geneInfoDictionary)))
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
def testMain(self):
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
wikipathways = wikipathwaysData()
wikipathways.getEverything()
r1 = random.choice(list(wikipathways.geneInfoDictionary.keys()))
r2 = random.choice(list(wikipathways.geneInfoDictionary.keys()))
r3 = random.choice(list(wikipathways.geneInfoDictionary.keys()))
print(wikipathways.geneInfoDictionary[r1])
print(wikipathways.geneInfoDictionary[r2])
print(wikipathways.geneInfoDictionary[r3])
print(wikipathways.geneInfoDictionary['ENSG00000139977'])
#print(wikipathways.geneInfoDictionary["path:hsa04530"])
time.sleep(3)
#idconvert.GeneConvert(wikipathways.geneInfoDictionary, "wiki")
wikipathways.write_myself_files('wiki')
wikicompoundnum = sql.createRampCompoundID(
wikipathways.metaboliteIDDictionary, "wiki", 0)
wikigenenum = sql.createRampGeneID(wikipathways.geneInfoDictionary,
"wiki", 0)
print("Write to file...")
wikipathwaysnumbers = sql.write(
wikipathways.metaboliteCommonName, wikipathways.pathwayDictionary,
wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.metabolitesLinkedToGenes,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, wikipathways.exoEndo,
wikipathways.tissueLocation, wikipathways.tissue, "wiki", 0, 0)
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
def testMain(self):
wiki = wikipathwaysData()
reactome = reactomeData()
kegg = KeggData()
sql = writeToSQL()
stat = getStatistics()
wiki.pathwaysWithGenesDictionary["WP254"] = ["geneA", "geneB"]
reactome.pathwaysWithGenesDictionary["R-HSA-109581"] = ["geneA", "geneD"]
kegg.pathwaysWithGenesDictionary["04210"] = ["geneC", "geneB"]
sql.rampGeneIDdictionary["geneA"] = "RAMP00001"
sql.rampGeneIDdictionary["geneB"] = "RAMP00002"
sql.rampGeneIDdictionary["geneC"] = "RAMP00003"
sql.rampGeneIDdictionary["geneD"] = "RAMP00001"
stat.Apoptosis(sql.rampGeneIDdictionary, wiki.pathwaysWithGenesDictionary, kegg.pathwaysWithGenesDictionary, reactome.pathwaysWithGenesDictionary)
def testMain(self):
kegg = KeggData()
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
# get database file
kegg.getDatabaseFiles()
#kegg.getDatabaseFiles2()
print('get pathways')
kegg.getPathways()
kegg.getPathways_with_genes()
print(len(kegg.pathwayDictionary))
print('get metabolites')
kegg.getMetabolites()
print('get synonyms and chebi')
kegg.getSynonymsAndCHEBI()
print(len(kegg.metaboliteIDDictionary))
print(kegg.metaboliteIDDictionary["C00002"])
print(kegg.metaboliteIDDictionary["C00001"])
'''
file = open("../misc/output/keggMetabolitesID.txt","wb")
for key in kegg.metaboliteIDDictionary:
file.write(key.encode("utf-8") +b"\n")
file.close()
'''
print('get genes')
kegg.getGenes()
print(len(kegg.geneInfoDictionary))
kegg.getGeneInfo()
kegg.getPathwayLinkedToGene()
file = open("../misc/output/keggGenesID.txt", "wb")
for key in kegg.geneInfoDictionary:
file.write(key.encode("utf-8") + b"\n")
file.close()
idconvert.GeneConvert(kegg.geneInfoDictionary, "kegg")
keggcompoundnum = sql.createRampCompoundID(kegg.metaboliteIDDictionary,
"kegg", 0)
kegggenenum = sql.createRampGeneID(kegg.geneInfoDictionary, "kegg", 0)
# Check duplicates
sql.checkForWithinDatabaseDuplicatesCompound(
kegg.metaboliteIDDictionary, "kegg")
sql.checkForWithinDatabaseDuplicatesGene(kegg.geneInfoDictionary,
"kegg")
# create ramp id
keggcompoundnum = sql.createRampCompoundID(kegg.metaboliteIDDictionary,
"kegg", 0)
kegggenenum = sql.createRampGeneID(kegg.geneInfoDictionary, "kegg", 0)
keggnumbers = sql.write(
kegg.metaboliteCommonName, kegg.pathwayDictionary,
kegg.pathwayCategory, kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary, kegg.pathwaysWithGenesDictionary,
kegg.metabolitesLinkedToGenes, kegg.geneInfoDictionary,
kegg.biofluidLocation, kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology, kegg.exoEndoDictionary,
kegg.exoEndo, kegg.tissueLocation, kegg.tissue, "kegg", 0, 0)
print('metaboliteIDdict number is ' +
str(len(kegg.metaboliteIDDictionary)))
print('GeneInfo number is ' + str(len(kegg.geneInfoDictionary)))
print('PathwayDict number is ' + str(len(kegg.pathwayDictionary)))
print('MetabolitesWithPath is ' +
str(len(kegg.metabolitesWithPathwaysDictionary)))
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
def runEverything(self, getDatabaseFiles=False):
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
hmdb = hmdbData()
wikipathways = wikipathwaysData()
reactome = reactomeData()
kegg = KeggData()
print(os.getcwd())
#pulls needed files from each database if true. Otherwise, assumes files already present. Default false.
if getDatabaseFiles:
kegg.getDatabaseFiles()
wikipathways.getDatabaseFiles()
reactome.getDatabaseFiles()
hmdb.getDatabaseFiles()
print("Getting HMDB Metabolites...")
hmdb.getMetaboliteOtherIDs()
print("Getting HMDB pathways and synonyms...")
hmdb.getPathwaysandSynonyms()
print("Getting HMDB genes...")
hmdb.getGenes()
print("Getting HMDB biofluid and cellular locations...")
hmdb.getBiofluidCellularLocationDisease()
print("Getting HMDB pathways links to genes ...")
hmdb.getPathwaysLinkedToGene()
print("Getting wikipathways...")
wikipathways.getEverything()
wikipathways.getCommonNameForChebi()
print("Getting reactome genes...")
reactome.getGenes()
print("Getting reactome metabolites...")
reactome.getMetabolites()
reactome.getCommonNameForChebi()
reactome.getCommonNameForGenes()
print("Getting kegg pathways...")
kegg.getPathways()
print("Getting kegg genes and metabolites...")
kegg.getMetabolites()
kegg.getSynonymsAndCHEBI()
kegg.getGenes()
kegg.getGeneInfo()
print("Converting gene ids...")
#Here are the identifiers that are present for each gene:
#kegg: keggid (mainID), 'Ensembl', 'HGNC', 'HPRD', 'NCBI-GeneID', 'NCBI-ProteinID', 'OMIM', 'UniProt', 'Vega', 'miRBase'
#wikipathways: (no mainID), 'Entrez', 'Enzyme Nomenclature', 'Uniprot (Uniprot-TrEMBL)
#hmdb: HMDB-protien-accession (mainID), 'Uniprot'
#reactome:Uniprot (mainID)
idconvert.GeneConvert(wikipathways.geneInfoDictionary, "wikipathways")
idconvert.GeneConvert(hmdb.geneInfoDictionary, "hmdb")
idconvert.GeneConvert(reactome.geneInfoDictionary, "reactome")
idconvert.GeneConvert(kegg.geneInfoDictionary, "kegg")
idconvert.GeneUniprotToHMDBP(wikipathways.geneInfoDictionary,
hmdb.geneInfoDictionary, "wikipathways")
idconvert.GeneUniprotToHMDBP(reactome.geneInfoDictionary,
hmdb.geneInfoDictionary, "reactome")
idconvert.GeneUniprotToHMDBP(kegg.geneInfoDictionary,
hmdb.geneInfoDictionary, "kegg")
print("Converting metabolite ids...")
idconvert.MetaboliteKeggIDToChebi(kegg.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary, "hmdb")
idconvert.MetaboliteChebiToHMDB(wikipathways.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary,
"wikipathways")
idconvert.MetaboliteChebiToHMDB(reactome.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary,
"reactome")
idconvert.MetaboliteChebiToHMDB(kegg.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary, "kegg")
#check for dups
print("Wikipathways compounds...")
sql.checkForWithinDatabaseDuplicatesCompound(
wikipathways.metaboliteIDDictionary, "wikipathways")
print("Wikipathways genes...")
sql.checkForWithinDatabaseDuplicatesGene(
wikipathways.geneInfoDictionary, "wikipathways")
print("Kegg compounds...")
sql.checkForWithinDatabaseDuplicatesCompound(
kegg.metaboliteIDDictionary, "kegg")
print("kegg genes...")
sql.checkForWithinDatabaseDuplicatesGene(kegg.geneInfoDictionary,
"kegg")
print("reactome compounds...")
sql.checkForWithinDatabaseDuplicatesCompound(
reactome.metaboliteIDDictionary, "reactome")
print("reactome genes...")
sql.checkForWithinDatabaseDuplicatesGene(reactome.geneInfoDictionary,
"reactome")
print("hmdb compounds...")
sql.checkForWithinDatabaseDuplicatesCompound(
hmdb.metaboliteIDDictionary, "hmdb")
print("hmdb genes...")
sql.checkForWithinDatabaseDuplicatesGene(hmdb.geneInfoDictionary,
"hmdb")
print('Generate compound id')
hmdbcompoundnum = sql.createRampCompoundID(hmdb.metaboliteIDDictionary,
"hmdb", 0)
wikicompoundnum = sql.createRampCompoundID(
wikipathways.metaboliteIDDictionary, "wiki", hmdbcompoundnum)
reactomecompoundnum = sql.createRampCompoundID(
reactome.metaboliteIDDictionary, "reactome", wikicompoundnum)
keggcompoundnum = sql.createRampCompoundID(kegg.metaboliteIDDictionary,
"kegg", reactomecompoundnum)
print('Generate gene id ...')
hmdbgenenum = sql.createRampGeneID(hmdb.geneInfoDictionary, "hmdb", 0)
wikigenenum = sql.createRampGeneID(wikipathways.geneInfoDictionary,
"wiki", hmdbgenenum)
reactomegenenum = sql.createRampGeneID(reactome.geneInfoDictionary,
"reactome", wikigenenum)
kegggenenum = sql.createRampGeneID(kegg.geneInfoDictionary, "kegg",
reactomegenenum)
print('Write to sql file...')
hmdbnumbers = sql.write(
hmdb.metaboliteCommonName, hmdb.pathwayDictionary,
hmdb.pathwayCategory, hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary, hmdb.pathwaysWithGenesDictionary,
hmdb.metabolitesLinkedToGenes, hmdb.geneInfoDictionary,
hmdb.biofluidLocation, hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology, hmdb.exoEndoDictionary,
hmdb.exoEndo, hmdb.tissueLocation, hmdb.tissue, "hmdb", 0, 0)
wikipathwaysnumbers = sql.write(
wikipathways.metaboliteCommonName, wikipathways.pathwayDictionary,
wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.metabolitesLinkedToGenes,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, wikipathways.exoEndo,
wikipathways.tissueLocation, wikipathways.tissue, "wiki",
hmdbnumbers[0], hmdbnumbers[1])
reactomenumbers = sql.write(
reactome.metaboliteCommonName, reactome.pathwayDictionary,
reactome.pathwayCategory,
reactome.metabolitesWithPathwaysDictionary,
reactome.metabolitesWithSynonymsDictionary,
reactome.metaboliteIDDictionary,
reactome.pathwaysWithGenesDictionary,
reactome.metabolitesLinkedToGenes, reactome.geneInfoDictionary,
reactome.biofluidLocation, reactome.biofluid,
reactome.cellularLocation, reactome.cellular,
reactome.pathwayOntology, reactome.exoEndoDictionary,
reactome.exoEndo, reactome.tissueLocation, reactome.tissue,
"reactome", wikipathwaysnumbers[0], wikipathwaysnumbers[1])
keggnumbers = sql.write(
kegg.metaboliteCommonName, kegg.pathwayDictionary,
kegg.pathwayCategory, kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary, kegg.pathwaysWithGenesDictionary,
kegg.metabolitesLinkedToGenes, kegg.geneInfoDictionary,
kegg.biofluidLocation, kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology, kegg.exoEndoDictionary,
kegg.exoEndo, kegg.tissueLocation, kegg.tissue, "kegg",
reactomenumbers[0], reactomenumbers[1])
print("Done ... for importing database")
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
stat.databaseContent(hmdb.pathwayDictionary, hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary,
hmdb.geneInfoDictionary, hmdb.biofluidLocation,
hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology,
hmdb.exoEndoDictionary, "hmdb")
stat.databaseContent(kegg.pathwayDictionary, kegg.pathwayCategory,
kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary,
kegg.pathwaysWithGenesDictionary,
kegg.geneInfoDictionary, kegg.biofluidLocation,
kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology,
kegg.exoEndoDictionary, "kegg")
stat.databaseContent(
reactome.pathwayDictionary, reactome.pathwayCategory,
reactome.metabolitesWithPathwaysDictionary,
reactome.metabolitesWithSynonymsDictionary,
reactome.metaboliteIDDictionary,
reactome.pathwaysWithGenesDictionary, reactome.geneInfoDictionary,
reactome.biofluidLocation, reactome.biofluid,
reactome.cellularLocation, reactome.cellular,
reactome.pathwayOntology, reactome.exoEndoDictionary, "reactome")
stat.databaseContent(
wikipathways.pathwayDictionary, wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, "wiki")
stat.Apoptosis(sql.rampGeneIDdictionary,
wikipathways.pathwaysWithGenesDictionary,
kegg.pathwaysWithGenesDictionary,
reactome.pathwaysWithGenesDictionary)
def testKeggToHMDB(self):
###############################################################################################
#IMPORTANT PART START
hmdb = hmdbData()
kegg = KeggData()
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
#metabolite mapping for hmdb
hmdb.metaboliteIDDictionary["HMDB00001"] = {
"chebi_id": "NA",
"drugbank_id": "NA",
"drugbank_metabolite_id": "NA",
"phenol_explorer_compound_id": "NA",
"phenol_explorer_metabolite_id": "NA",
"foodb_id": "FDB012119",
"knapsack_id": "NA",
"chemspider_id": "83153",
"kegg_id": "C14814",
"biocyc_id": "CPD-1823",
"bigg_id": "NA",
"wikipidia": "NA",
"nugowiki": "NA",
"metagene": "NA",
"metlin_id": "3741",
"pubchem_compound_id": "92105",
"het_id": "HIC",
"hmdb_id": ["HMDB00001"],
"CAS": "NA"
}
#metabolite mapping for kegg
kegg.metaboliteIDDictionary["C14814"] = {
"chebi_id": ["34131"],
"drugbank_id": "NA",
"drugbank_metabolite_id": "NA",
"phenol_explorer_compound_id": "NA",
"phenol_explorer_metabolite_id": "NA",
"foodb_id": "NA",
"knapsack_id": "NA",
"chemspider_id": "NA",
"kegg_id": "C14814",
"biocyc_id": "NA",
"bigg_id": "NA",
"wikipidia": "NA",
"nugowiki": "NA",
"metagene": "NA",
"metlin_id": "NA",
"pubchem_compound_id": "NA",
"het_id": "NA",
"hmdb_id": "NA",
"CAS": "NA"
}
idconvert.MetaboliteKeggIDToChebi(kegg.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary, "hmdb")
idconvert.MetaboliteChebiToHMDB(kegg.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary, "kegg")
#IMPORTANT PART END
######################################################################################################
#Pathway names
kegg.pathwayDictionary["00010"] = "Glycolysis / Gluconeogenesis"
kegg.pathwayDictionary["00020"] = "Citrate cycle (TCA cycle)"
kegg.pathwayDictionary["00520"] = "Fake Pathway Name One"
kegg.pathwayDictionary["00524"] = "Fake Pathway Name Two"
kegg.pathwayDictionary["00540"] = "Fake Pathway Name Three"
kegg.pathwayDictionary["00550"] = "Fake Pathway Name Four"
kegg.pathwayDictionary["00030"] = "Fake Pathway Name Five"
kegg.pathwayDictionary["00040"] = "Fake Pathway Name Six"
kegg.pathwayDictionary["00053"] = "Fake Pathway Name Seven"
kegg.pathwayDictionary["00250"] = "Fake Pathway Name Eight"
kegg.pathwayDictionary["00260"] = "Fake Pathway Name Nine"
#Pathway categories
kegg.pathwayCategory["00010"] = "Metabolism"
kegg.pathwayCategory["00020"] = "Human Diseases"
kegg.pathwayCategory["00520"] = "Cellular Processes"
kegg.pathwayCategory["00524"] = "Human Diseases"
kegg.pathwayCategory["00540"] = "Human Diseases"
kegg.pathwayCategory["00550"] = "Metabolism"
kegg.pathwayCategory["00030"] = "Human Diseases"
kegg.pathwayCategory["00040"] = "Cellular Processes"
kegg.pathwayCategory["00053"] = "Metabolism"
kegg.pathwayCategory["00250"] = "Human Diseases"
kegg.pathwayCategory["00260"] = "Cellular Processes"
#metabolites linked with pathways
kegg.metabolitesWithPathwaysDictionary["C14814"] = ["00020"]
#metabolites linkes with synonyms
kegg.metabolitesWithSynonymsDictionary["C14814"] = [
"MetaboliteSynonym1"
]
#pathway to gene id
kegg.pathwaysWithGenesDictionary["00010"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00020"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00520"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00524"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00540"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00550"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00030"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00040"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00053"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00250"] = ["geneA", "geneB"]
kegg.pathwaysWithGenesDictionary["00260"] = ["geneA", "geneB"]
#gene to geneinfo
kegg.geneInfoDictionary["geneA"] = {
'common_name': 'Apple',
'kegg': 'NA',
'Ensembl': 'ENSG00000127481',
'HGNC': '30313',
'HPRD': 'NA',
'NCBI-GeneID': '23352',
'NCBI-ProteinID': 'NP_065816',
'OMIM': '609890',
'UniProt': 'Q5T4S7',
'Vega': 'OTTHUMG00000002498',
'miRBase': 'NA',
'HMDB_protien_accession': 'NA',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
kegg.geneInfoDictionary["geneB"] = {
'common_name': 'Banana',
'kegg': 'NA',
'Ensembl': 'ENSG00000100320',
'HGNC': '9906',
'HPRD': 'NA',
'NCBI-GeneID': '23543',
'NCBI-ProteinID': 'NP_065816',
'OMIM': '612149',
'UniProt': 'O43251',
'Vega': 'OTTHUMG00000150585',
'miRBase': 'NA',
'HMDB_protien_accession': 'NA',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
hmdb.metabolitesWithSynonymsDictionary["HMDB00001"] = [
"1 Methylhistidine", "1-Methyl-L-histidine", "Pi-methylhistidine"
]
hmdb.metabolitesWithPathwaysDictionary["HMDB00001"] = [
"SMP00716", "SMP00006"
]
hmdb.pathwayDictionary["SMP00716"] = "Thyroid hormone synthesis"
hmdb.pathwayDictionary["SMP00006"] = "Tyrosine Metabolism"
hmdb.pathwayDictionary["SMP00001"] = "Pathway1"
hmdb.pathwayDictionary["SMP00002"] = "Pathway2"
hmdb.pathwayDictionary["SMP00816"] = "Pathway3"
hmdb.pathwayCategory["SMP00716"] = "NA"
hmdb.pathwayCategory["SMP00006"] = "NA"
hmdb.pathwayCategory["SMP00001"] = "NA"
hmdb.pathwayCategory["SMP00002"] = "NA"
hmdb.pathwayCategory["SMP00816"] = "NA"
hmdb.pathwaysWithGenesDictionary["SMP00716"] = ["Q96KN2", "uniprot1"]
hmdb.pathwaysWithGenesDictionary["SMP00006"] = ["Q96KN2", "uniprot1"]
hmdb.pathwaysWithGenesDictionary["SMP00001"] = ["Q96KN2", "uniprot1"]
hmdb.pathwaysWithGenesDictionary["SMP00002"] = ["Q96KN2", "uniprot1"]
hmdb.pathwaysWithGenesDictionary["SMP00816"] = ["Q96KN2", "uniprot1"]
hmdb.geneInfoDictionary["Q96KN2"] = {
'common_name': 'CNDP1',
'kegg': 'NA',
'Ensembl': 'NA',
'HGNC': 'NA',
'HPRD': 'NA',
'NCBI-GeneID': 'NA',
'NCBI-ProteinID': 'NA',
'OMIM': 'NA',
'UniProt': 'Q96KN2',
'Vega': 'NA',
'miRBase': 'NA',
'HMDB_protien_accession': 'HMDBP00473',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
hmdb.geneInfoDictionary["uniprot1"] = {
'common_name': 'genename1',
'kegg': 'NA',
'Ensembl': 'NA',
'HGNC': 'NA',
'HPRD': 'NA',
'NCBI-GeneID': 'NA',
'NCBI-ProteinID': 'NA',
'OMIM': 'NA',
'UniProt': 'uniprot1',
'Vega': 'NA',
'miRBase': 'NA',
'HMDB_protien_accession': 'HMDBP00321',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
hmdb.biofluidLocation["HMDB00001"] = [
"Blood", "Cerebrospinal Fluid (CSF)", "Feces", "Saliva", "Urine"
]
hmdb.exoEndoDictionary["HMDB00001"] = ["Food"]
hmdb.biofluid["Blood"] = "placeholder"
hmdb.biofluid["Cerebrospinal Fluid (CSF)"] = "placeholder"
hmdb.biofluid["Feces"] = "placeholder"
hmdb.biofluid["Saliva"] = "placeholder"
hmdb.biofluid["Urine"] = "placeholder"
hmdb.cellularLocation["HMDB00001"] = ["Cytoplasm", "Location1"]
hmdb.cellular["Cytoplasm"] = "placeholder"
hmdb.cellular["Location1"] = "placeholder"
hmdb.cellular["Location2"] = "placeholder"
hmdb.cellular["Location3"] = "placeholder"
sql.write(kegg.pathwayDictionary, kegg.pathwayCategory,
kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary,
kegg.pathwaysWithGenesDictionary, kegg.geneInfoDictionary,
kegg.biofluidLocation, kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology, kegg.exoEndoDictionary,
"kegg", 0, 0)
sql.write(hmdb.pathwayDictionary, hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary, hmdb.geneInfoDictionary,
hmdb.biofluidLocation, hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology, hmdb.exoEndoDictionary,
"hmdb", 0, 0)
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases)
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases)
def testMain(self):
sql = writeToSQL()
hmdb = hmdbData()
print(hmdb.day)
# If does not have database file
hmdb.getDatabaseFiles()
idconvert = IDconversion()
stat = getStatistics()
#print(hmdb.pathwaysWithGenesDictionary['SMP00172'])
#print(len(hmdb.pathwaysWithGenesDictionary['SMP00172']))
#print(hmdb.pathwaysWithGenesDictionary['00240'])
#print(len(hmdb.pathwaysWithGenesDictionary['00240']))
# hmdb.getAllId()
print("Getting HMDB Metabolites...")
hmdb.getMetaboliteOtherIDs()
print(len(hmdb.metaboliteIDDictionary))
print(hmdb.metaboliteIDDictionary["HMDB0000538"])
print(hmdb.metaboliteIDDictionary["HMDB0000122"])
print("Getting HMDB pathways and synonyms...")
hmdb.getPathwaysandSynonyms()
print('Has pathways ...')
print('How many pathways relationship ...')
#print(str(len(hmdb.metabolitesWithPathwaysDictionary)))
print("Getting HMDB genes...")
hmdb.getGenes()
print("Getting HMDB biofluid and cellular locations...")
#hmdb.getBiofluidCellularLocationDisease()
hmdb.getPathwaysLinkedToGene()
print("Writing to files...")
print("output each metabolites has how many pathways ...")
#idconvert.GeneConvert(hmdb.geneInfoDictionary, "hmdb")
print("hmdb compounds...")
sql.checkForWithinDatabaseDuplicatesCompound(hmdb.metaboliteIDDictionary, "hmdb")
print("hmdb genes...")
sql.checkForWithinDatabaseDuplicatesGene(hmdb.geneInfoDictionary, "hmdb")
hmdbcompoundnum = sql.createRampCompoundID(hmdb.metaboliteIDDictionary, "hmdb", 0)
hmdbgenenum = sql.createRampGeneID(hmdb.geneInfoDictionary, "hmdb", 0)
sql.write(hmdb.metaboliteCommonName,
hmdb.pathwayDictionary,
hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary,
hmdb.metabolitesLinkedToGenes,
hmdb.geneInfoDictionary,
hmdb.biofluidLocation,
hmdb.biofluid,
hmdb.cellularLocation,
hmdb.cellular,
hmdb.pathwayOntology,
hmdb.exoEndoDictionary,
hmdb.exoEndo,
hmdb.tissueLocation,
hmdb.tissue,
"hmdb",
0, 0)
print('Compound number is ' + str(len(hmdb.metaboliteIDDictionary)))
print('Gene number is ' + str(len(hmdb.geneInfoDictionary)))
print('Pathway number is ' + str(len(hmdb.pathwayDictionary)))
print('Pathway that have Gene with it ' + str(len(hmdb.pathwaysWithGenesDictionary)))
def testreactomeToHMDB(self):
hmdb = hmdbData()
reactome = reactomeData()
sql = writeToSQL()
idconvert = IDconversion()
stat = getStatistics()
#metabolite mapping for hmdb
hmdb.metaboliteIDDictionary["HMDB00001"] = {
"chebi_id": ["C14814"],
"drugbank_id": "NA",
"drugbank_metabolite_id": "NA",
"phenol_explorer_compound_id": "NA",
"phenol_explorer_metabolite_id": "NA",
"foodb_id": "FDB012119",
"knapsack_id": "NA",
"chemspider_id": "83153",
"kegg_id": "C14814",
"biocyc_id": "CPD-1823",
"bigg_id": "NA",
"wikipidia": "NA",
"nugowiki": "NA",
"metagene": "NA",
"metlin_id": "3741",
"pubchem_compound_id": "92105",
"het_id": "HIC",
"hmdb_id": ["HMDB00001"],
"CAS": "NA"
}
#metabolite mapping for kegg
reactome.metaboliteIDDictionary["C14814"] = {
"chebi_id": ["C14814"],
"drugbank_id": "NA",
"drugbank_metabolite_id": "NA",
"phenol_explorer_compound_id": "NA",
"phenol_explorer_metabolite_id": "NA",
"foodb_id": "NA",
"knapsack_id": "NA",
"chemspider_id": "NA",
"kegg_id": "NA",
"biocyc_id": "NA",
"bigg_id": "NA",
"wikipidia": "NA",
"nugowiki": "NA",
"metagene": "NA",
"metlin_id": "NA",
"pubchem_compound_id": "NA",
"het_id": "NA",
"hmdb_id": "NA",
"CAS": "NA"
}
hmdb.geneInfoDictionary["Q96KN2"] = {
'common_name': 'genename1',
'kegg': 'NA',
'Ensembl': 'NA',
'HGNC': 'NA',
'HPRD': 'NA',
'NCBI-GeneID': 'NA',
'NCBI-ProteinID': 'NA',
'OMIM': 'NA',
'UniProt': ['Q96KN2'],
'Vega': 'NA',
'miRBase': 'NA',
'HMDB_protien_accession': 'HMDBP00321',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
reactome.geneInfoDictionary["Q96KN2"] = {
'common_name': 'NA',
'kegg': 'NA',
'Ensembl': 'NA',
'HGNC': 'NA',
'HPRD': 'NA',
'NCBI-GeneID': 'NA',
'NCBI-ProteinID': 'NA',
'OMIM': 'NA',
'UniProt': ['Q96KN2'],
'Vega': 'NA',
'miRBase': 'NA',
'HMDB_protien_accession': 'NA',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
hmdb.metabolitesWithSynonymsDictionary["HMDB00001"] = [
"1 Methylhistidine", "1-Methyl-L-histidine", "Pi-methylhistidine"
]
hmdb.metabolitesWithPathwaysDictionary["HMDB00001"] = [
"SMP00716", "SMP00006"
]
hmdb.pathwayDictionary["SMP00716"] = "Thyroid hormone synthesis"
hmdb.pathwayDictionary["SMP00006"] = "Tyrosine Metabolism"
hmdb.pathwayDictionary["SMP00001"] = "Pathway1"
hmdb.pathwayDictionary["SMP00002"] = "Pathway2"
hmdb.pathwayDictionary["SMP00816"] = "Pathway3"
hmdb.pathwayCategory["SMP00716"] = "NA"
hmdb.pathwayCategory["SMP00006"] = "NA"
hmdb.pathwayCategory["SMP00001"] = "NA"
hmdb.pathwayCategory["SMP00002"] = "NA"
hmdb.pathwayCategory["SMP00816"] = "NA"
hmdb.pathwaysWithGenesDictionary["SMP00716"] = ["Q96KN2"]
hmdb.pathwaysWithGenesDictionary["SMP00006"] = ["Q96KN2"]
hmdb.pathwaysWithGenesDictionary["SMP00001"] = ["Q96KN2"]
hmdb.pathwaysWithGenesDictionary["SMP00002"] = ["Q96KN2"]
hmdb.pathwaysWithGenesDictionary["SMP00816"] = ["Q96KN2"]
hmdb.geneInfoDictionary["Q96KN2"] = {
'common_name': 'CNDP1',
'kegg': 'NA',
'Ensembl': 'NA',
'HGNC': 'NA',
'HPRD': 'NA',
'NCBI-GeneID': 'NA',
'NCBI-ProteinID': 'NA',
'OMIM': 'NA',
'UniProt': ['Q96KN2'],
'Vega': 'NA',
'miRBase': 'NA',
'HMDB_protien_accession': 'HMDBP00473',
'Entrez': 'NA',
'Enzyme Nomenclature': 'NA'
}
hmdb.biofluidLocation["HMDB00001"] = [
"Blood", "Cerebrospinal Fluid (CSF)", "Feces", "Saliva", "Urine"
]
hmdb.biofluid["Blood"] = "placeholder"
hmdb.biofluid["Cerebrospinal Fluid (CSF)"] = "placeholder"
hmdb.biofluid["Feces"] = "placeholder"
hmdb.biofluid["Saliva"] = "placeholder"
hmdb.biofluid["Urine"] = "placeholder"
hmdb.cellularLocation["HMDB00001"] = ["Cytoplasm", "Location1"]
hmdb.cellular["Cytoplasm"] = "placeholder"
hmdb.cellular["Location1"] = "placeholder"
hmdb.cellular["Location2"] = "placeholder"
hmdb.cellular["Location3"] = "placeholder"
hmdb.exoEndoDictionary["HMDB00001"] = "Food"
reactome.pathwayDictionary[
"R-HSA-210745"] = "Citrate cycle (TCA cycle)"
#Pathway categories
reactome.pathwayCategory["R-HSA-210745"] = "Human Diseases"
#metabolites linked with pathways
reactome.metabolitesWithPathwaysDictionary["C14814"] = ["R-HSA-210745"]
#metabolites linkes with synonyms
reactome.metabolitesWithSynonymsDictionary["C14814"] = [
"MetaboliteSynonym1"
]
#pathway to gene id
reactome.pathwaysWithGenesDictionary["R-HSA-210745"] = ["Q96KN2"]
idconvert.MetaboliteChebiToHMDB(reactome.metaboliteIDDictionary,
hmdb.metaboliteIDDictionary,
"reactome")
idconvert.GeneUniprotToHMDBP(reactome.geneInfoDictionary,
hmdb.geneInfoDictionary, "hmdb")
hmdbcompoundnum = sql.createRampCompoundID(hmdb.metaboliteIDDictionary,
"hmdb", 0)
reactomecompoundnum = sql.createRampCompoundID(
reactome.metaboliteIDDictionary, "reactome", hmdbcompoundnum)
hmdbgenenum = sql.createRampGeneID(hmdb.geneInfoDictionary, "hmdb", 0)
reactomegenenum = sql.createRampGeneID(reactome.geneInfoDictionary,
"reactome", hmdbgenenum)
sql.write(reactome.pathwayDictionary, reactome.pathwayCategory,
reactome.metabolitesWithPathwaysDictionary,
reactome.metabolitesWithSynonymsDictionary,
reactome.metaboliteIDDictionary,
reactome.pathwaysWithGenesDictionary,
reactome.geneInfoDictionary, reactome.biofluidLocation,
reactome.biofluid, reactome.cellularLocation,
reactome.cellular, reactome.pathwayOntology,
reactome.exoEndoDictionary, "reactome", 0, 0)
sql.write(hmdb.pathwayDictionary, hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary, hmdb.geneInfoDictionary,
hmdb.biofluidLocation, hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology, hmdb.exoEndoDictionary,
"hmdb", 0, 0)
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
stat.databaseContent(hmdb.pathwayDictionary, hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary,
hmdb.geneInfoDictionary, hmdb.biofluidLocation,
hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology,
hmdb.exoEndoDictionary, "hmdb")
def runEverything(self, getDatabaseFiles=True):
sql = writeToSQL()
stat = getStatistics()
hmdb = hmdbData()
wikipathways = WikipathwaysRDF()
reactome = reactomeData()
kegg = KeggData()
# works based on your computer, setup working directory
os.chdir('../main/')
#kegg.getEverything(False)
#print("KEGG Wonder")
hmdb.getEverything(True)
print("Getting wikipathways...")
wikipathways.getEverything(True)
print("Getting reactome...")
reactome.getEverything(True)
print("Getting kegg...")
#Here are the identifiers that are present for each gene:
#kegg: keggid (mainID), 'Ensembl', 'HGNC', 'HPRD', 'NCBI-GeneID', 'NCBI-ProteinID', 'OMIM', 'UniProt', 'Vega', 'miRBase'
#wikipathways: (no mainID), 'Entrez', 'Enzyme Nomenclature', 'Uniprot (Uniprot-TrEMBL)
#hmdb: HMDB-protien-accession (mainID), 'Uniprot'
#reactome:Uniprot (mainID)
print('Generate compound id')
hmdbcompoundnum = sql.createRampCompoundID(hmdb.metaboliteIDDictionary,
"hmdb", 0)
print("hmdbcompoundnum: ", hmdbcompoundnum)
keggcompoundnum = sql.createRampCompoundID(kegg.metaboliteIDDictionary,
"kegg", hmdbcompoundnum)
wikicompoundnum = sql.createRampCompoundID(
wikipathways.metaboliteIDDictionary, "wiki", keggcompoundnum)
print("wikicompoundnum: ", wikicompoundnum)
reactomecompoundnum = sql.createRampCompoundID(
reactome.metaboliteIDDictionary, "reactome", wikicompoundnum)
print('Generate gene id ...')
hmdbgenenum = sql.createRampGeneID(hmdb.geneInfoDictionary, "hmdb", 0)
kegggenenum = sql.createRampGeneID(kegg.geneInfoDictionary, "kegg",
hmdbgenenum)
wikigenenum = sql.createRampGeneID(wikipathways.geneInfoDictionary,
"wiki", kegggenenum)
reactomegenenum = sql.createRampGeneID(reactome.geneInfoDictionary,
"reactome", wikigenenum)
print(" hmdbgenenum ", hmdbgenenum, " kegggenenum ", kegggenenum,
" wikigenenum ", wikigenenum, " reactomegenenum ",
reactomegenenum)
print('Write to sql file...')
hmdbnumbers = sql.write(
hmdb.metaboliteCommonName, hmdb.pathwayDictionary,
hmdb.pathwayCategory, hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary, hmdb.pathwaysWithGenesDictionary,
hmdb.metabolitesLinkedToGenes, hmdb.geneInfoDictionary,
hmdb.biofluidLocation, hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology, hmdb.exoEndoDictionary,
hmdb.exoEndo, hmdb.tissueLocation, hmdb.tissue, hmdb.metaInchi,
"hmdb", 0, 0)
wikipathwaysnumbers = sql.write(
wikipathways.metaboliteCommonName, wikipathways.pathwayDictionary,
wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.metabolitesLinkedToGenes,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, wikipathways.exoEndo,
wikipathways.tissueLocation, wikipathways.tissue, dict(), "wiki",
hmdbnumbers[0], hmdbnumbers[1])
reactomenumbers = sql.write(
reactome.metaboliteCommonName, reactome.pathwayDictionary,
reactome.pathwayCategory,
reactome.metabolitesWithPathwaysDictionary,
reactome.metabolitesWithSynonymsDictionary,
reactome.metaboliteIDDictionary,
reactome.pathwaysWithGenesDictionary,
reactome.metabolitesLinkedToGenes, reactome.geneInfoDictionary,
reactome.biofluidLocation, reactome.biofluid,
reactome.cellularLocation, reactome.cellular,
reactome.pathwayOntology, reactome.exoEndoDictionary,
reactome.exoEndo, reactome.tissueLocation, reactome.tissue, dict(),
"reactome", wikipathwaysnumbers[0], wikipathwaysnumbers[1])
keggnumbers = sql.write(
kegg.metaboliteCommonName, kegg.pathwayDictionary,
kegg.pathwayCategory, kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary, kegg.pathwaysWithGenesDictionary,
kegg.metabolitesLinkedToGenes, kegg.geneInfoDictionary,
kegg.biofluidLocation, kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology, kegg.exoEndoDictionary,
kegg.exoEndo, kegg.tissueLocation, kegg.tissue, dict(), "kegg",
reactomenumbers[0], reactomenumbers[1])
print("Done ... for importing database")
print("Compound:")
stat.analyteOverlaps(sql.rampCompoundIdInWhichDatabases,
sql.rampCompoundIDdictionary, "Compound")
print("\n")
print("Gene:")
stat.analyteOverlaps(sql.rampGeneIdInWhichDatabases,
sql.rampGeneIDdictionary, "Gene")
stat.databaseContent(hmdb.pathwayDictionary, hmdb.pathwayCategory,
hmdb.metabolitesWithPathwaysDictionary,
hmdb.metabolitesWithSynonymsDictionary,
hmdb.metaboliteIDDictionary,
hmdb.pathwaysWithGenesDictionary,
hmdb.geneInfoDictionary, hmdb.biofluidLocation,
hmdb.biofluid, hmdb.cellularLocation,
hmdb.cellular, hmdb.pathwayOntology,
hmdb.exoEndoDictionary, "hmdb")
stat.databaseContent(kegg.pathwayDictionary, kegg.pathwayCategory,
kegg.metabolitesWithPathwaysDictionary,
kegg.metabolitesWithSynonymsDictionary,
kegg.metaboliteIDDictionary,
kegg.pathwaysWithGenesDictionary,
kegg.geneInfoDictionary, kegg.biofluidLocation,
kegg.biofluid, kegg.cellularLocation,
kegg.cellular, kegg.pathwayOntology,
kegg.exoEndoDictionary, "kegg")
stat.databaseContent(
reactome.pathwayDictionary, reactome.pathwayCategory,
reactome.metabolitesWithPathwaysDictionary,
reactome.metabolitesWithSynonymsDictionary,
reactome.metaboliteIDDictionary,
reactome.pathwaysWithGenesDictionary, reactome.geneInfoDictionary,
reactome.biofluidLocation, reactome.biofluid,
reactome.cellularLocation, reactome.cellular,
reactome.pathwayOntology, reactome.exoEndoDictionary, "reactome")
stat.databaseContent(
wikipathways.pathwayDictionary, wikipathways.pathwayCategory,
wikipathways.metabolitesWithPathwaysDictionary,
wikipathways.metabolitesWithSynonymsDictionary,
wikipathways.metaboliteIDDictionary,
wikipathways.pathwaysWithGenesDictionary,
wikipathways.geneInfoDictionary, wikipathways.biofluidLocation,
wikipathways.biofluid, wikipathways.cellularLocation,
wikipathways.cellular, wikipathways.pathwayOntology,
wikipathways.exoEndoDictionary, "wiki")
from hmdbData import hmdbData
from writeToSQL import writeToSQL
from reactomeData import reactomeData
from getStatistics import getStatistics
stat = getStatistics()
import unittest
class TestHMDBMain(unittest.TestCase):
def testMain(self):
sql = writeToSQL()
hmdb = hmdbData()
reactome = reactomeData()
hmdb.metaboliteIDDictionary["HMDB00001"] = {
"chebi_id": "NA",
"drugbank_id": "NA",
"drugbank_metabolite_id": "NA",
"phenol_explorer_compound_id": "NA",
"phenol_explorer_metabolite_id": "NA",
"foodb_id": "FDB012119",
"knapsack_id": "NA",
"chemspider_id": "83153",
"kegg_id": "C14814",
"biocyc_id": "CPD-1823",
"bigg_id": "NA",
"wikipidia": "NA",
"nugowiki": "NA",
"metagene": "NA",