diff SNRQK2.py @ 0:2547394443a0

"planemo upload commit 8b4c59e523d28c30368aebfa0416d9ff8e27d257"
author jasmine_amir
date Thu, 09 Jun 2022 19:29:02 -0400
parents
children 1ab67c0c0054
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/SNRQK2.py	Thu Jun 09 19:29:02 2022 -0400
@@ -0,0 +1,37 @@
+#!/usr/bin/env python3
+# coding: utf-8
+###########################################################
+###########################################################
+## Jasmine Amirzadegan
+## 2022 APRIL 14
+###########################################################
+## SNRQC.py:
+## compute QC metrics specific to SSQuAWK v4 + workflows
+## usage: python SNRQC.py intermediateSSQuAWKfile.txt
+## python 3.7
+###########################################################
+import pandas as pd
+import sys
+
+fn = sys.argv[1]
+df = pd.read_csv(fn, sep = "\t", header = 0)
+
+
+
+if (df['Sample'].str.contains('negativeControl')).any():
+    m = df.loc[ (df['Sample'].str.contains('negativeControl')) ]
+    noise = m['readsAlignPassFilt']
+    SNR = []
+
+    for i in df['readsAlignPassFilt']:
+        SNR.append(i/noise.item())
+        #[float(j) for j in SNR]
+    df['SNR'] = SNR
+
+else:
+    df['SNR'] = "NA"
+
+#print(df)
+#fn1 = fn.split("/")[1]
+#df.to_csv('test-data/snrqk_result' + fn1 + '.tsv', sep="\t")
+df.to_csv('snrqk_result.tsv', sep='\t')