geneid2symbol = {}
# Get xlsx filename where data is stored
din_xlsx = r"C:\Users\krishna\Downloads\padj_converted.xlsx" ###excel file containing 3 columns:
### gene_symbols (our test data), their respective ESENMBL gene ids, and their p adj values (test_data)
# Read data
if os.path.isfile(din_xlsx):
import xlrd
book = xlrd.open_workbook(din_xlsx)
pg = book.sheet_by_index(0)
for r in range(pg.nrows):
symbol, geneid, pval = [pg.cell_value(r, c) for c in range(pg.ncols)]
if geneid:
geneid2symbol[int(geneid)] = symbol
print('READ: {XLSX}'.format(XLSX=din_xlsx))
else:
raise RuntimeError('CANNOT READ: {XLSX}'.format(XLSX=fin_xlsx))
### 5. Run Gene Ontology Enrichment Analysis (GOEA)
# 'p_' means "pvalue". 'fdr_bh' is the multipletest method we are currently using.
geneids_study = geneid2symbol.keys()
goea_results_all = goeaobj.run_study(geneids_study)
goea_results_sig = [r for r in goea_results_all if r.p_fdr_bh < 0.05]
### to export our analysis results one file with only gene symbols and second file with gene ids
goeaobj.wr_xlsx("GO_symbols.xlsx", goea_results_sig, itemid2name=geneid2symbol)
goeaobj.wr_xlsx("GO_geneids.xlsx", goea_results_sig)
def pullGOenrichment(inputFile, project):
GeneID2nt_hum = genes_NCBI_9606_ProteinCoding.GENEID2NT
obo_fname = download_go_basic_obo()
fin_gene2go = download_ncbi_associations()
obodag = GODag("go-basic.obo")
# Read NCBI's gene2go. Store annotations in a list of namedtuples
objanno = Gene2GoReader(fin_gene2go, taxids=[9606])
# Get namespace2association where:
# namespace is:
# BP: biological_process
# MF: molecular_function
# CC: cellular_component
# assocation is a dict:
# key: NCBI GeneID
# value: A set of GO IDs associated with that gene
ns2assoc = objanno.get_ns2assc()
for nspc, id2gos in ns2assoc.items():
print("{NS} {N:,} annotated human genes".format(NS=nspc,
N=len(id2gos)))
print(len(GeneID2nt_hum))
goeaobj = GOEnrichmentStudyNS(
GeneID2nt_hum.keys(), # List of human protein-coding genes
ns2assoc, # geneid/GO associations
obodag, # Ontologies
propagate_counts=False,
alpha=0.05, # default significance cut-off
methods=['fdr_bh']) # defult multipletest correction method
geneid2symbol = {}
with open(inputFile, 'r') as infile:
input_genes = csv.reader(infile)
for line in input_genes:
geneid = line[0]
symbol = line[1]
if geneid:
geneid2symbol[int(geneid)] = symbol
infile.close()
geneids_study = geneid2symbol.keys()
goea_results_all = goeaobj.run_study(geneids_study)
goea_results_sig = [r for r in goea_results_all if r.p_fdr_bh < 0.05]
import collections as cx
ctr = cx.Counter([r.NS for r in goea_results_sig])
print('Significant results[{TOTAL}] = {BP} BP + {MF} MF + {CC} CC'.format(
TOTAL=len(goea_results_sig),
BP=ctr['BP'], # biological_process
MF=ctr['MF'], # molecular_function
CC=ctr['CC'])) # cellular_component
goeaobj.wr_xlsx("Data/go_enrichment" + project + ".csv", goea_results_sig)
goeaobj.wr_txt("Data/go_enrichment" + project + ".txt", goea_results_sig)