jasmine_amir@9: #!/dep/_conda/bin/python
jasmine_amir@0: # coding: utf-8
jasmine_amir@0: ###########################################################
jasmine_amir@0: ###########################################################
jasmine_amir@0: ## Jasmine Amirzadegan
jasmine_amir@0: ## 2022 APRIL 14
jasmine_amir@0: ###########################################################
jasmine_amir@0: ## SNRQC.py:
jasmine_amir@0: ## compute QC metrics specific to SSQuAWK v4 + workflows
jasmine_amir@0: ## usage: python SNRQC.py intermediateSSQuAWKfile.txt
jasmine_amir@0: ## python 3.7
jasmine_amir@0: ###########################################################
jasmine_amir@0: import pandas as pd
jasmine_amir@0: import sys
jasmine_amir@0: 
jasmine_amir@0: fn = sys.argv[1]
jasmine_amir@0: df = pd.read_csv(fn, sep = "\t", header = 0)
jasmine_amir@0: 
jasmine_amir@0: 
jasmine_amir@0: 
jasmine_amir@0: if (df['Sample'].str.contains('negativeControl')).any():
jasmine_amir@0:     m = df.loc[ (df['Sample'].str.contains('negativeControl')) ]
jasmine_amir@0:     noise = m['readsAlignPassFilt']
jasmine_amir@0:     SNR = []
jasmine_amir@0: 
jasmine_amir@0:     for i in df['readsAlignPassFilt']:
jasmine_amir@0:         SNR.append(i/noise.item())
jasmine_amir@0:         #[float(j) for j in SNR]
jasmine_amir@0:     df['SNR'] = SNR
jasmine_amir@0: 
jasmine_amir@0: else:
jasmine_amir@0:     df['SNR'] = "NA"
jasmine_amir@0: 
jasmine_amir@0: #print(df)
jasmine_amir@0: #fn1 = fn.split("/")[1]
jasmine_amir@0: #df.to_csv('test-data/snrqk_result' + fn1 + '.tsv', sep="\t")
jasmine_amir@0: df.to_csv('snrqk_result.tsv', sep='\t')