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#Script to integrate TBL scores to Pancan, CCLE, PACAWG clinical_sample files | |
import os | |
import pandas as pd | |
dh_path = "/Users/madupurr/Github/datahub/public" | |
tbl_scores_path = "/Users/madupurr/Desktop/TBL_scores/TBL_scores.txt" | |
tbl_scores = pd.read_csv(tbl_scores_path ,sep='\t',header = None) |
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import sys | |
import os | |
study_dir = "/Users/madupurr/Desktop/genie_subset/impact_subset" | |
output_dir = "/Users/madupurr/Desktop/genie_subset/corrected_ids" | |
files = os.listdir(study_dir) | |
def extract_header(study_dir, filename): | |
with open(study_dir+'/'+filename, 'r') as infile: |
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#!/usr/bin/python | |
import sys | |
import os | |
import optparse | |
# Script to remove duplicate maf records based on the 8 key columns. | |
# Calculates VAF for each record and picks the record with high VAF | |
# Formula for VAF = t_alt_count / (t_ref_count + t_alt_count) | |
ERROR_FILE = sys.stderr |
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"""Convert data in | |
python code to convert | |
P-0000246-T05 LTB 2 | |
P-0000246-T05 NOTCH4 2 | |
P-0002556-T03 KMT2A 2 | |
P-0003309-T02 ATM -2 | |
to | |
Gene P-0000246-T05 P-0002556-T03 P-0003309-T02 |
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