Merge branch 'master' of https://github.com/nygenome/Conpair

modules/ContaminationMarker.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python
 
 #
 # 2015-09-02
@@ -73,7 +73,7 @@ def parse_mpileup_line(line, min_map_quality=0, min_base_quality=0):
     if min_map_quality > 0:
         verbose_lines = line[6].split(',')
         mapqs = [v.split('@')[-1] for v in verbose_lines]
-        mapqs_above_threshold = set([i for i in xrange(0, len(mapqs)) if int(mapqs[i]) >= min_map_quality])
+        mapqs_above_threshold = set([i for i in range(0, len(mapqs)) if int(mapqs[i]) >= min_map_quality])
 
     indexes_A = find_all_positions_of_char(bases, 'A')
     indexes_C = find_all_positions_of_char(bases, 'C')
@@ -173,7 +173,7 @@ def baseQ2int(baseQ_string, scaling_factor=33):
 
 
 def find_all_positions_of_char(s, char):
-    indexes = [i for i in xrange(0, len(s)) if s[i] == char]
+    indexes = [i for i in range(0, len(s)) if s[i] == char]
     return(indexes)
 
 

modules/ContaminationModel.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python
 
 #
 # 2015-09-02
@@ -32,7 +32,7 @@
 def create_conditional_likelihood_of_base_dict(checkpoints):
 
     D = defaultdict(lambda: defaultdict(dict))
-    for bq in xrange(0, baseQ_max+1):
+    for bq in range(0, baseQ_max+1):
         Q = phred2prob(bq)/3
 
         f_AAAA_A = lambda x: (1-Q)
@@ -71,12 +71,12 @@ def create_conditional_likelihood_of_base_dict(checkpoints):
 def likelihood_per_marker(A, Scores, checkpoints, ref_basequals, alt_basequals):
 
     for bq in ref_basequals:
-        for i in xrange(0, len(checkpoints)):
+        for i in range(0, len(checkpoints)):
             v = checkpoints[i]
             ref_part = [Scores['AAAA_A'][v][bq], Scores['AABB_A'][v][bq], Scores['AABA_A'][v][bq], Scores['ABAB_A'][v][bq], Scores['ABAA_A'][v][bq], Scores['ABAA_B'][v][bq], Scores['AAAA_B'][v][bq], Scores['AABB_B'][v][bq], Scores['AABA_B'][v][bq]]
             A[i] += ref_part
     for bq in alt_basequals:
-        for i in xrange(0, len(checkpoints)):
+        for i in range(0, len(checkpoints)):
             v = checkpoints[i]
             alt_part = [Scores['AAAA_B'][v][bq], Scores['AABB_B'][v][bq], Scores['AABA_B'][v][bq], Scores['ABAB_B'][v][bq], Scores['ABAA_B'][v][bq], Scores['ABAA_A'][v][bq], Scores['AAAA_A'][v][bq], Scores['AABB_A'][v][bq], Scores['AABA_A'][v][bq]]
             A[i] += alt_part
@@ -88,16 +88,15 @@ def calculate_contamination_likelihood(checkpoints, Data, Scores):
     D = np.zeros([len(checkpoints), 1],dtype='float64')
     for marker_data in Data:
         A = np.zeros([len(checkpoints), 9],dtype='float64')
-        for i in xrange(0, len(checkpoints)):
+        for i in range(0, len(checkpoints)):
             A[i] += marker_data[0]
         A = likelihood_per_marker(A, Scores, checkpoints, marker_data[1], marker_data[2])
-        for i in xrange(0, len(checkpoints)):
+        for i in range(0, len(checkpoints)):
             D[i] += log10p(sum([pow(10,x ) for x in A[i]]))
 
     return(D)
 
-def apply_brents_algorithm(Data, Scores, (x1, x2, x3)):
-
+def apply_brents_algorithm(Data, Scores, x1, x2, x3):
     def f(x):
         if type(x) is np.ndarray:
             x = x[0]

modules/Genotypes.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python
 
 #
 # 2015-10-08

modules/MathOperations.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python2.7
+#!/usr/bin/env python
 
 #
 # 2016-02-29
@@ -27,6 +27,6 @@ def phred2prob(Q):
 def log10p(f):
 
     if f < 1e-323:
-	return(-324)
+        return(-324)
     else:
-	return(np.log10(f))
+        return(np.log10(f))

scripts/estimate_tumor_normal_contamination.py

@@ -92,7 +92,7 @@ def drange(start, stop, step):
 Data = []
 for line in file:
     if line.startswith("[REDUCE RESULT]"):
-	continue   
+        continue
     pileup = ContaminationMarker.parse_mpileup_line(line, min_map_quality=MMQ)
     try:
         marker = Markers[pileup.chrom + ":" + pileup.pos]
@@ -140,7 +140,7 @@ def drange(start, stop, step):
 
 ### SEARCHING THE SPACE AROUND ARGMAX - Brent's algorithm
 
-optimal_val = ContaminationModel.apply_brents_algorithm(Data, Scores, (x1, x2, x3))
+optimal_val = ContaminationModel.apply_brents_algorithm(Data, Scores, x1, x2, x3)
 
 ### PRINTING THE NORMAL RESULTS
 
@@ -212,7 +212,7 @@ def drange(start, stop, step):
 
 ### SEARCHING THE SPACE AROUND ARGMAX - Brent's algorithm
 
-optimal_val = ContaminationModel.apply_brents_algorithm(Data, Scores, (x1, x2, x3))
+optimal_val = ContaminationModel.apply_brents_algorithm(Data, Scores, x1, x2, x3)
 
 ### PRINTING THE TUMOR RESULTS
 

scripts/run_gatk_pileup_for_sample.py

@@ -76,7 +76,7 @@
 if opts.temp_dir_java:
     JAVA_TEMP = "-Djava.io.tmpdir={}".format(opts.temp_dir_java)
     if not os.path.isdir(opts.temp_dir_java):
-        os.makedirs(opts.temp_dir_java, 0770)
+        os.makedirs(opts.temp_dir_java, 770)
 else:
     JAVA_TEMP = ""
 
@@ -95,7 +95,7 @@
             for line in source_file:
                 if line.startswith("chr"):
                     tmp_source.write(line[3:])
-            	else:
+                else:
                     tmp_source.write(line)
 
     move(tmp_source.name, source_file.name)

scripts/verify_concordance.py

@@ -84,10 +84,10 @@
 
 
 if opts.outfile == "-":
-    print round(float(concordant)/(concordant+discordant), 3)
-    print "Based on " + str(concordant+discordant) + "/" + str(len(Markers)) + " markers (coverage per marker threshold: " + str(COVERAGE_THRESHOLD) + " reads)"
-    print "Minimum mappinq quality: " + str(MMQ)
-    print "Minimum base quality: " + str(MBQ)
+    print(round(float(concordant)/(concordant+discordant), 3))
+    print("Based on " + str(concordant+discordant) + "/" + str(len(Markers)) + " markers (coverage per marker threshold: " + str(COVERAGE_THRESHOLD) + " reads)")
+    print("Minimum mappinq quality: " + str(MMQ))
+    print("Minimum base quality: " + str(MBQ))
 else:
     outfile = open(opts.outfile, 'w')
     outfile.write("Concordance: "+ str(round(100.0*float(concordant)/(concordant+discordant), 2)) + "%\n")