def run_mccoil(barcode_file_lines, maf_file_lines=None, verbose=False):
## init barcode set
barcode_set = Barcode.SetOfBarcodes()
barcode_set.readBarcodeFileLines(barcode_file_lines)
# validate
is_valid_barcode_set, err_msg = barcode_set.validate()
if not is_valid_barcode_set:
print err_msg
return ([])
## init mafs
if not maf_file_lines:
mafs = barcode_set.computeMAFFromBarcodes(1)
else:
mafs = MAF.MAF()
mafs.readMAFFileLines(maf_file_lines)
mafs_R_vector = robjects.Vector(mafs.minor_allele_freqs())
# validate
is_valid_mafs, err_msg = mafs.validate()
if not is_valid_mafs:
print err_msg
return ({})
## compute zygosity matrix, then convert to R DataFrame
zygosity_matrix = barcode_set.to_zygosity_matrix(mafs,
header=True,
index=True)
if verbose: print(zygosity_matrix)
data = to_R_zygosity_df(zygosity_matrix)
if verbose: print(data)
## import MCCOIL
mccoil_R_code = open(mccoil_R, 'r').read()
mccoil = SignatureTranslatedAnonymousPackage(mccoil_R_code, 'mccoil')
## compute result
result = mccoil.McCOIL_categorical(data, P=mafs_R_vector)
#print result
## get sites/samples
sites, samples = list(result[-2]), list(result[-1])
## get maf/coi predictions, which map 1-to-1 sites/samples
# (i.e. maf_prediction[i] is prediction for site[i])
maf_predictions, coi_predictions = list(result[6]), list(result[5])
return ({
'mafs': zip(sites, maf_predictions),
'cois': zip(samples, coi_predictions)
})
