diff --git a/rpkm.py b/rpkm.py
index 77e195a0b189a145900230b1458d966aae3ea374..4895f5f5b95191f076471a6ae06be172768a65aa 100755
--- a/rpkm.py
+++ b/rpkm.py
@@ -47,7 +47,7 @@ def rpkm(peak_file,aln_file,exp_name,columns):
     columns.append(exp_name)
     ## RPKM  =   numReads / (geneLength/1000 * totalNumReads/1,000,000 )
     peak_counts = peak_file.multi_bam_coverage(bams=[aln_file])
-    total_counts = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(aln_file,,split_lines=True))])
+    total_counts = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(aln_file,split_lines=True)])
     rpkm = peak_counts.each(normalized_to_length, 3, float(math.pow(10,9))/total_counts).saveas("test.bed")
     rpkm_df = rpkm.to_dataframe()
     #os.remove('test.bed')
@@ -61,7 +61,7 @@ def rpkm_strand(peak_file,aln_file,exp_name,columns):
     columns.append(exp_name)
     ## RPKM  =   numReads / (geneLength/1000 * totalNumReads/1,000,000 )
     peak_counts = peak_file.multi_bam_coverage(bams=[aln_file],s=True)
-    total_counts = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(aln_file,,split_lines=True))])
+    total_counts = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(aln_file,split_lines=True)])
     rpkm = peak_counts.each(normalized_to_length, 6, float(math.pow(10,9))/float(total_counts)).saveas("test.bed")
     rpkm_df = rpkm.to_dataframe()
     #os.remove('test.bed')
diff --git a/rpkm_gro.py b/rpkm_gro.py
index cae162dbf7eaf8c79dea1e4af275d6d2f853ab75..4cf65f29dc80e0349e2a6ca99ad75a2f76d39f67 100755
--- a/rpkm_gro.py
+++ b/rpkm_gro.py
@@ -48,7 +48,6 @@ def rpkm(peak_file,aln_file,exp_name,columns):
     ## RPKM  =   numReads / (geneLength/1000 * totalNumReads/1,000,000 )
     peak_counts = peak_file.multi_bam_coverage(bams=[aln_file])
     total_counts = reduce(lambda x, y: x + y, [ int(l.rstrip('\n').split('\t')[2]) for l in pysam.idxstats(aln_file,split_lines=True)])
-    print total_counts
     rpkm = peak_counts.each(normalized_to_length, 3, float(math.pow(10,9))/total_counts).saveas("test.bed")
     rpkm_df = rpkm.to_dataframe()
     #os.remove('test.bed')