diff --git a/rpkm.py b/rpkm.py
index bcc842c39541c84eebd4eed99716f3cf8d68e553..77e195a0b189a145900230b1458d966aae3ea374 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)])
+    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)])
+    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 8f817eb801b187995385d3afcbf9548ace19f385..ee3c56aefe43d95716765a94707514f9097b028f 100755
--- a/rpkm_gro.py
+++ b/rpkm_gro.py
@@ -47,7 +47,8 @@ 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)])
+    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')
@@ -61,7 +62,7 @@ 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)])
+    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')
@@ -112,7 +113,6 @@ def main():
     # Write out RPKM matrix
     filtered_peaks = filtered_rpkm[columns]
     filtered_rpkm.to_csv(args.factor + '_filtered_peaks.tsv', header=True, index=None, sep='\t')
-    peak_rpkm_only_sum.to_csv(args.factor + '_sum.tsv', header=True, index=True, sep='\t')
     pybedtools.BedTool.from_dataframe(filtered_peaks).saveas(args.factor + '_filtered_peaks.bed')