if __name__ == "__main__":
# Load required modules
import sys, os, json
sys.path.append('../')
import comet as C, run_comet_simple as RC, run_exhaustive as RE
# Hard-coded results of earlier runs
trueMCMC = [["CDK4(A),CDKN2A(D),TP53 EGFR,PDGFRA(A),PTEN(D)", 36, 30.44954813369114], ["CDK4(A),CDKN2A(D),TP53 EGFR,PTEN,PTEN(D)", 47, 30.31560877273872], ["CDK4(A),CDKN2A(D),TP53 EGFR,PDGFRA(A),RB1(D)", 6, 28.487778643951266], ["CDK4(A),CDKN2A(D),TP53 PDGFRA(A),PTEN,PTEN(D)", 2, 27.986374758844306], ["CDK4(A),CDKN2A(D),TP53 EGFR,PTEN(D),RB1(D)", 1, 27.207736477342962], ["CDK4(A),CDKN2A(D),TP53 EGFR,MDM4(A),RB1(D)", 1, 26.9059191024149], ["CDK4(A),CDKN2A(D),RB1(D) EGFR,PDGFRA(A),PTEN(D)", 3, 26.35048099140887], ["CDK4(A),CDKN2A(D),RB1(D) EGFR,PTEN,PTEN(D)", 1, 26.216541630456447], ["CDK4(A),CDKN2A(D),TP53 MDM4(A),PTEN(D),RB1(D)", 1, 24.99799710738864], ["CDK4(A),CDKN2A(D),TP53 EGFR,MDM4(A),PTEN", 1, 24.910765737533954], ["CDK4(A),CDKN2A(D),TP53 PDGFRA(A),PTEN,RB1(D)", 1, 24.633365961904023]]
trueExhaustive = [[["CDK4(A)", "CDKN2A(D)", "TP53"], 0.0, 24.61051], [["CDK4(A)", "CDKN2A(D)", "RB1(D)"], 0.0, 20.51144], [["CDKN2A(D)", "RB1(D)", "TP53"], 0.0, 15.30173], [["CDKN2A(D)", "PDGFRA(A)", "TP53"], 0.0, 14.35459], [["CDK4(A)", "CDKN2A(D)", "PTEN(D)"], 1e-05, 11.92406], [["CDKN2A(D)", "PTEN(D)", "TP53"], 1e-05, 11.90466], [["CDK4(A)", "CDKN2A(D)", "EGFR"], 1e-05, 11.49421], [["CDKN2A(D)", "MDM4(A)", "TP53"], 2e-05, 10.68068], [["CDK4(A)", "CDKN2A(D)", "MDM4(A)"], 4e-05, 10.07425], [["CDKN2A(D)", "PTEN", "TP53"], 7e-05, 9.55559], [["CDKN2A(D)", "EGFR", "TP53"], 0.00015, 8.82747], [["CDK4(A)", "CDKN2A(D)", "PTEN"], 0.00035, 7.96747], [["CDK4(A)", "CDKN2A(D)", "PDGFRA(A)"], 0.00048, 7.6389], [["EGFR", "PDGFRA(A)", "PTEN(D)"], 0.00291, 5.83904], [["EGFR", "PTEN", "PTEN(D)"], 0.00333, 5.7051], [["EGFR", "PDGFRA(A)", "RB1(D)"], 0.02071, 3.87727], [["CDK4(A)", "PTEN", "PTEN(D)"], 0.02471, 3.70061], [["CDK4(A)", "EGFR", "RB1(D)"], 0.03291, 3.41404], [["PDGFRA(A)", "PTEN", "PTEN(D)"], 0.03419, 3.37587], [["CDK4(A)", "EGFR", "PTEN(D)"], 0.04911, 3.01377], [["PTEN", "PTEN(D)", "TP53"], 0.0636, 2.75514], [["EGFR", "PTEN(D)", "RB1(D)"], 0.07448, 2.59723], [["EGFR", "PTEN(D)", "TP53"], 0.07453, 2.59651], [["CDKN2A(D)", "EGFR", "RB1(D)"], 0.08983, 2.40983], [["MDM4(A)", "PTEN(D)", "TP53"], 0.09648, 2.33843], [["EGFR", "MDM4(A)", "RB1(D)"], 0.10072, 2.29541], [["CDKN2A(D)", "EGFR", "PTEN"], 0.12616, 2.0702], [["PTEN", "PTEN(D)", "RB1(D)"], 0.13519, 2.00109], [["EGFR", "MDM4(A)", "PDGFRA(A)"], 0.15149, 1.88723], [["CDK4(A)", "EGFR", "PDGFRA(A)"], 0.17147, 1.76336], [["EGFR", "MDM4(A)", "TP53"], 0.18851, 1.66862], [["MDM4(A)", "PTEN", "PTEN(D)"], 0.19338, 1.64308], [["CDKN2A(D)", "MDM4(A)", "RB1(D)"], 0.20638, 1.57806], [["CDK4(A)", "EGFR", "PTEN"], 0.20825, 1.56901], [["PDGFRA(A)", "PTEN(D)", "RB1(D)"], 0.21409, 1.54137], [["CDK4(A)", "PTEN(D)", "RB1(D)"], 0.23869, 1.43258], [["PDGFRA(A)", "PTEN(D)", "TP53"], 0.24857, 1.39204], [["CDKN2A(D)", "PDGFRA(A)", "PTEN"], 0.27821, 1.27939], [["MDM4(A)", "PDGFRA(A)", "TP53"], 0.29567, 1.21851], [["PTEN(D)", "RB1(D)", "TP53"], 0.3062, 1.18352], [["CDKN2A(D)", "PDGFRA(A)", "RB1(D)"], 0.31956, 1.14081], [["CDK4(A)", "EGFR", "MDM4(A)"], 0.3235, 1.12854], [["CDKN2A(D)", "PTEN", "RB1(D)"], 0.41747, 0.87355], [["CDK4(A)", "EGFR", "TP53"], 0.44446, 0.81089], [["MDM4(A)", "PDGFRA(A)", "RB1(D)"], 0.4468, 0.80566], [["CDK4(A)", "MDM4(A)", "RB1(D)"], 0.47088, 0.75315], [["MDM4(A)", "RB1(D)", "TP53"], 0.47495, 0.74454], [["EGFR", "PDGFRA(A)", "TP53"], 0.53346, 0.62837], [["EGFR", "PDGFRA(A)", "PTEN"], 0.53346, 0.62837], [["MDM4(A)", "PDGFRA(A)", "PTEN(D)"], 0.54257, 0.61144], [["EGFR", "MDM4(A)", "PTEN(D)"], 0.58204, 0.54122], [["CDKN2A(D)", "PTEN(D)", "RB1(D)"], 0.59467, 0.51974], [["CDK4(A)", "PTEN(D)", "TP53"], 0.60326, 0.50541], [["MDM4(A)", "PDGFRA(A)", "PTEN"], 0.62282, 0.47349], [["MDM4(A)", "PTEN", "TP53"], 0.62456, 0.4707], [["CDK4(A)", "MDM4(A)", "TP53"], 0.65547, 0.42241], [["MDM4(A)", "PTEN(D)", "RB1(D)"], 0.67876, 0.38749], [["CDKN2A(D)", "MDM4(A)", "PTEN"], 0.68465, 0.37884], [["CDK4(A)", "PDGFRA(A)", "PTEN(D)"], 0.70878, 0.34421], [["CDKN2A(D)", "EGFR", "PDGFRA(A)"], 0.7178, 0.33157], [["CDK4(A)", "MDM4(A)", "PTEN(D)"], 0.71914, 0.3297], [["EGFR", "RB1(D)", "TP53"], 0.73762, 0.30432], [["EGFR", "MDM4(A)", "PTEN"], 0.74063, 0.30026], [["CDK4(A)", "PDGFRA(A)", "RB1(D)"], 0.75931, 0.27534], [["CDKN2A(D)", "PTEN", "PTEN(D)"], 0.77636, 0.25314], [["PDGFRA(A)", "RB1(D)", "TP53"], 0.80285, 0.21958], [["CDK4(A)", "MDM4(A)", "PTEN"], 0.82971, 0.18668], [["CDKN2A(D)", "EGFR", "PTEN(D)"], 0.83641, 0.17864], [["CDKN2A(D)", "EGFR", "MDM4(A)"], 0.83641, 0.17864], [["CDKN2A(D)", "MDM4(A)", "PTEN(D)"], 0.8707, 0.13846], [["CDKN2A(D)", "PDGFRA(A)", "PTEN(D)"], 0.8759, 0.1325], [["CDKN2A(D)", "MDM4(A)", "PDGFRA(A)"], 0.8759, 0.1325], [["EGFR", "PTEN", "RB1(D)"], 0.88503, 0.12214], [["EGFR", "PTEN", "TP53"], 0.88751, 0.11933], [["CDK4(A)", "PTEN", "TP53"], 0.88937, 0.11725], [["CDK4(A)", "PDGFRA(A)", "PTEN"], 0.91005, 0.09426], [["CDK4(A)", "PTEN", "RB1(D)"], 0.91538, 0.08841], [["PTEN", "RB1(D)", "TP53"], 0.95692, 0.04404], [["CDK4(A)", "MDM4(A)", "PDGFRA(A)"], 0.95942, 0.04142], [["CDK4(A)", "RB1(D)", "TP53"], 0.96379, 0.03688], [["PDGFRA(A)", "PTEN", "RB1(D)"], 0.9774, 0.02286], [["PDGFRA(A)", "PTEN", "TP53"], 0.98084, 0.01935], [["MDM4(A)", "PTEN", "RB1(D)"], 0.98887, 0.01119], [["CDK4(A)", "PDGFRA(A)", "TP53"], 0.9892, 0.01086]]
# Run CoMEt MCMC using a fixed seed
seed = 23
mcmcArgs = [ "-m", "../example_datasets/gbm/GBM.m2", "-o", "tmp-mcmc",
"-g", "../example_datasets/gbm/GBM.glst", "-N", "10000",
"--seed", str(seed), "-mf", "30", "-ks", "3", "3", "--noviz"]
mcmcResults = RC.run(RC.get_parser().parse_args(mcmcArgs))
if os.path.exists("tmp-mcmc.para.k33.10K.1.json"):
os.unlink("tmp-mcmc.para.k33.10K.1.json")
if os.path.exists("tmp-mcmc-sum.k33.10K.1.tsv"):
os.unlink("tmp-mcmc.sum.k33.10K.1.tsv")
# Run exhaustive
exhaustArgs = ["-m", "../example_datasets/gbm/GBM.m2", "-o", "tmp",
"-g", "../example_datasets/gbm/GBM.glst", "-k", "3",
"-mf", "30"]
exhaustResults = RE.run(RE.get_parser().parse_args(exhaustArgs))
exhaustResults = [ (genes, round(phi, 5), round(score, 5)) for genes, phi, score in exhaustResults]
if os.path.exists("tmp-k3-exact-exhaustive.tsv"):
os.unlink("tmp-k3-exact-exhaustive.tsv")
def runComet(cometArgs):
return RC.run( RC.get_parser().parse_args(cometArgs) )
def run(args):
# Set up the arguments for a general CoMEt run on real data
realOutputDir = "{}/comet-results".format(args.output_directory)
realCometArgs = []
permuteFlags = ["-np", "--parallel", "--keep_temp_files", "-o"]
for i, arg in enumerate(sys.argv[1:]):
if arg not in permuteFlags and sys.argv[i] not in permuteFlags:
realCometArgs.append(arg)
realCometArgs += ["-o", realOutputDir, "--noviz"]
# perform simple run without viz first.
results = runComet(realCometArgs)
# Load mutation data using Multi-Dendrix and output as a temporary file
realMutations = C.load_mutation_data(args.mutation_matrix,
args.patient_file, args.gene_file,
args.min_freq, args.subtype)
m, n, genes, patients, geneToCases, patientToGenes, subtypes = realMutations
if args.verbose:
print(f'* Mutation data: {m} genes x {n} patients')
# Construct bipartite graph from mutation data
if args.verbose: print('* Creating bipartite graph...')
G = C.construct_mutation_graph(geneToCases, patientToGenes)
if args.verbose:
print('\t- Graph has', len(G.edges()), 'edges among', len(G.nodes()),
'nodes.')
# reset the arguments for a general CoMEt run on permuted matrices
cometArgs = []
permuteFlags = ["-np", "--parallel", "--keep_temp_files", "-m", "-o"]
for i, arg in enumerate(sys.argv[1:]):
if arg not in permuteFlags and sys.argv[i] not in permuteFlags:
cometArgs.append(arg)
cometArgs.append('--noviz')
# Create a permuted matrix, and then run it through CoMEt
import tempfile
arguments = []
if args.keep_temp_files:
directory = args.output_directory
else:
directory = tempfile.mkdtemp(dir=".", prefix=".tmp")
# Generate random seeds for each permutation
random.seed(args.seed)
seeds = [
random.randint(0, 2**31 - 1) for _ in range(args.num_permutations)
]
for i, seed in enumerate(seeds):
# Print simple progress bar
sys.stdout.write(
"* Running CoMEt on permuted matrices... {}/{}\r".format(
i + 1, args.num_permutations))
sys.stdout.flush()
# Create a permuted dataset and save it a temporary file
mutations = C.permute_mutation_data(G, genes, patients, seed, args.Q)
_, _, _, _, geneToCases, patientToGenes = mutations
adj_list = [
p + "\t" + "\t".join(sorted(patientToGenes[p])) for p in patients
]
permutation_file = "{}/permuted-matrix-{}.m2".format(directory, i + 1)
with open(permutation_file, 'w') as outfile:
outfile.write('\n'.join(adj_list))
# Add the new arguments
permuteArgs = list(map(str, cometArgs))
permuteArgs += ["-m", permutation_file]
permuteArgs += [
"-o",
"{}/comet-results-on-permutation-{}".format(directory, i + 1)
]
arguments.append(permuteArgs)
if args.parallel:
pool = mp.Pool(25)
results = pool.map(runComet, arguments)
pool.close()
pool.join()
else:
results = [runComet(permuteArgs) for permuteArgs in arguments]
# Find the maximum test statistic on the permuted datasets
from itertools import islice
maxStat = 0
for rf in [
rf for rf in os.listdir(directory)
if rf.startswith("comet-results-on-permutation")
]:
for df in [
df for df in os.listdir("{}/{}/results".format(directory, rf))
if df.endswith(".tsv")
]:
with open("{}/{}/results/{}".format(directory, rf, df)) as infile:
for line in islice(infile, 1, 2):
score = float(line.split("\t")[1])
if score > maxStat:
maxStat = score
print("*" * 80)
print("Number of permutations:", args.num_permutations)
print("Max statistic:", maxStat)
# Prepare comet results on real, mutation data, and output directory for viz
for rf in [
rf for rf in os.listdir("{}/results/".format(realOutputDir))
if (not rf.startswith('.') and rf.endswith(".tsv"))
]:
resultsTable = [
l.rstrip() for l in open("{}/results/{}".format(realOutputDir, rf))
]
realMutations = (m, n, genes, patients, geneToCases, patientToGenes)
outputDirViz = realOutputDir + "/viz/"
C.ensure_dir(outputDirViz)
# Perform visualization
C.output_comet_viz(RC.get_parser().parse_args(realCometArgs), realMutations, \
resultsTable, maxStat, args.num_permutations)
# Destroy the temporary directory if necessary
if not args.keep_temp_files:
import shutil
shutil.rmtree(directory)
def run( args ):
# Set up the arguments for a general CoMEt run on real data
realOutputDir = "{}/comet-results".format(args.output_directory)
realCometArgs = []
permuteFlags = ["-np", "--parallel", "--keep_temp_files", "-o"]
for i, arg in enumerate(sys.argv[1:]):
if arg not in permuteFlags and sys.argv[i] not in permuteFlags:
realCometArgs.append( arg )
realCometArgs += [ "-o", realOutputDir, "--noviz"]
# perform simple run without viz first.
results = runComet(realCometArgs)
# Load mutation data using Multi-Dendrix and output as a temporary file
realMutations = C.load_mutation_data(args.mutation_matrix, args.patient_file,
args.gene_file, args.min_freq, args.subtype)
m, n, genes, patients, geneToCases, patientToGenes, subtypes = realMutations
if args.verbose:
print('* Mutation data: %s genes x %s patients' % (m, n))
# Construct bipartite graph from mutation data
if args.verbose: print("* Creating bipartite graph...")
G = C.construct_mutation_graph(geneToCases, patientToGenes)
if args.verbose:
print('\t- Graph has', len( G.edges() ), 'edges among', len( G.nodes() ), 'nodes.')
# reset the arguments for a general CoMEt run on permuted matrices
cometArgs = []
permuteFlags = ["-np", "--parallel", "--keep_temp_files", "-m", "-o"]
for i, arg in enumerate(sys.argv[1:]):
if arg not in permuteFlags and sys.argv[i] not in permuteFlags:
cometArgs.append( arg )
cometArgs.append('--noviz')
# Create a permuted matrix, and then run it through CoMEt
import tempfile
arguments = []
if args.keep_temp_files:
directory = args.output_directory
else:
directory = tempfile.mkdtemp(dir=".", prefix=".tmp")
# Generate random seeds for each permutation
random.seed(args.seed)
seeds = [ random.randint(0, 2**31-1) for _ in range(args.num_permutations) ]
for i, seed in enumerate(seeds):
# Print simple progress bar
sys.stdout.write("* Running CoMEt on permuted matrices... {}/{}\r".format(i+1, args.num_permutations))
sys.stdout.flush()
# Create a permuted dataset and save it a temporary file
mutations = C.permute_mutation_data(G, genes, patients, seed, args.Q)
_, _, _, _, geneToCases, patientToGenes = mutations
adj_list = [ p + "\t" + "\t".join( sorted(patientToGenes[p]) ) for p in patients ]
permutation_file = "{}/permuted-matrix-{}.m2".format(directory, i+1)
with open(permutation_file, 'w') as outfile: outfile.write('\n'.join(adj_list))
# Add the new arguments
permuteArgs = list(map(str, cometArgs))
permuteArgs += [ "-m", permutation_file ]
permuteArgs += [ "-o", "{}/comet-results-on-permutation-{}".format(directory, i+1)]
arguments.append( permuteArgs )
if args.parallel:
pool = mp.Pool(25)
results = pool.map(runComet, arguments)
pool.close()
pool.join()
else:
results = [ runComet(permuteArgs) for permuteArgs in arguments ]
# Find the maximum test statistic on the permuted datasets
from itertools import islice
maxStat = 0
for rf in [ rf for rf in os.listdir(directory) if rf.startswith("comet-results-on-permutation") ]:
for df in [df for df in os.listdir("{}/{}/results".format(directory, rf) ) if df.endswith(".tsv")]:
with open("{}/{}/results/{}".format(directory, rf, df)) as infile:
for line in islice(infile, 1, 2):
score = float(line.split("\t")[1])
if score > maxStat:
maxStat = score
print("*" * 80)
print("Number of permutations:", args.num_permutations)
print("Max statistic:", maxStat)
# Prepare comet results on real, mutation data, and output directory for viz
for rf in [rf for rf in os.listdir( "{}/results/".format(realOutputDir) ) if rf.endswith(".tsv")]:
resultsTable = [l.rstrip() for l in open( "{}/results/{}".format(realOutputDir, rf))]
realMutations = (m, n, genes, patients, geneToCases, patientToGenes )
outputDirViz = realOutputDir + "/viz/"
C.ensure_dir(outputDirViz)
# Perform visualization
C.output_comet_viz(RC.get_parser().parse_args(realCometArgs), realMutations,
resultsTable, maxStat, args.num_permutations)
# Destroy the temporary directory if necessary
if not args.keep_temp_files:
import shutil
shutil.rmtree(directory)
def runComet(cometArgs):
return RC.run(RC.get_parser().parse_args(cometArgs))