def main(argv):
'''
command line parameters:
neofile - text file with neoantigen data (supplementary data)
alignmentDirectory - folder with precomputed alignments
a - midpoint parameter of the logistic function, alignment score threshold
k - slope parameter of the logistic function
outfile - path to a file where to output neoantigen fitness computation
'''
neofile=argv[1]
alignmentDirectory=argv[2]
a=float(argv[3])
k=float(argv[4])
outfile=sys.argv[5]
nmerl=float(argv[6])
[neoantigens,samples]=readNeoantigens(neofile, nmerl)
#Compute TCR-recognition probabilities for all neoantigens
aligner=Aligner()
for sample in samples:
xmlpath=alignmentDirectory+"/neoantigens_"+sample+"_iedb.xml"
aligner.readAllBlastAlignments(xmlpath)
aligner.computeR(a, k)
#Write neoantigen recognition potential
of=open(outfile,'w')
header=["NeoantigenID","Mutation","Sample","MutatedPeptide","ResidueChangeClass","MutantPeptide","WildtypePeptide","A","R","Excluded","NeoantigenRecognitionPotential"]
header="\t".join(header)
of.write(header+"\n")
for i in neoantigens:
neoantigen=neoantigens[i]
w=neoantigen.getWeight() #excludes neoantigens that mutated from a nonhydrophobic residue on position 2 or 9
A=neoantigens[i].getA() #MHC amplitude A
mtpeptide=neoantigens[i].mtPeptide #mutant peptide
wtpeptide=neoantigens[i].wtPeptide
R=aligner.getR(i)
# Residue change:
# HH: from hydrophobic to hydrophobic,
# NN: from non-hydrophobic to non-hydrophobic
# HN: from hydrophobic to non-hydrophobic,
# NH: from non-hydrophobic to hydrophobic
# other (WW, WH, HW, NW, WN) which include aminoacids without a clear classification
residueChange=neoantigen.residueChange
fitnessCost=A*R*w
l=[i, neoantigen.mid, neoantigen.sample, neoantigen.position, residueChange, mtpeptide, wtpeptide, A,R, 1-w, fitnessCost]#, neoAlignment, epitopeAlignment, score, species]
l="\t".join(map(lambda s: str(s),l))
of.write(l+"\n")
def main(argv):
'''
command line parameters:
neofile - text file with neoantigen data (supplementary data)
alignmentDirectory - folder with precomputed alignments
a - midpoint parameter of the logistic function, alignment score threshold
k - slope parameter of the logistic function
outfile - path to a file where to output neoantigen fitness computation
'''
neofile=argv[1]
alignmentDirectory=argv[2]
a=float(argv[3])
k=float(argv[4])
outfile=sys.argv[5]
xmlpath=sys.argv[6]
[neoantigens,samples]=readNeoantigens(neofile)
#Compute TCR-recognition probabilities for all neoantigens
aligner=Aligner()
#for sample in samples:
# xmlpath=alignmentDirectory+"/neoantigens_"+sample+"_iedb.xml"
# aligner.readAllBlastAlignments(xmlpath)
#xmlpath=alignmentDirectory+"/neoantigens_5NSAK_iedb.xml"
#xmlpath="/scratch/eknodel/cohen_melanoma/validated_peptides/3466/3466_lukszablast.out"
aligner.readAllBlastAlignments(xmlpath)
aligner.computeR(a, k)
#Write neoantigen recognition potential
of=open(outfile,'w')
#header=["NeoantigenID","Mutation","Sample","MutatedPeptide","ResidueChangeClass","MutantPeptide","WildtypePeptide","A","R","Excluded","NeoantigenRecognitionPotential"]
header=["NeoantigenID","Mutation","Sample","MutantPeptide","WildtypePeptide","A","R","w","wc","Fitness"]
header="\t".join(header)
of.write(header+"\n")
for i in neoantigens:
#print(i)
neoantigen=neoantigens[i]
#print(neoantigen)
w=neoantigen.getHydro() #calculates neoantigen fraction based on Luksza definition
wc = neoantigen.getConsortiumHydro() #Calcuculates neoantigen fraction based on Consortium's definition (https://doi.org/10.1016/j.cell.2020.09.015)
A=neoantigens[i].getA() #MHC amplitude A
#print(A)
mtpeptide=neoantigens[i].mtPeptide #mutant peptide
wtpeptide=neoantigens[i].wtPeptide
R=aligner.getR(i)
#print(R)
# Residue change:
# HH: from hydrophobic to hydrophobic,
# NN: from non-hydrophobic to non-hydrophobic
# HN: from hydrophobic to non-hydrophobic,
# NH: from non-hydrophobic to hydrophobic
# other (WW, WH, HW, NW, WN) which include aminoacids without a clear classification
#residueChange=neoantigen.residueChange
#print(residueChange)
fitnessCost=A*R*w
#fitnessCost=A*R
#l=[i, neoantigen.mid, neoantigen.sample, neoantigen.position, residueChange, mtpeptide, wtpeptide, A,R, 1-w, fitnessCost]#, neoAlignment, epitopeAlignment, score, species]
l=[i, neoantigen.mid, neoantigen.sample, mtpeptide, wtpeptide, A,R,w,wc, fitnessCost]#, neoAlignment, epitopeAlignment, score, species]
l="\t".join(map(lambda s: str(s),l))
of.write(l+"\n")
