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hub / github.com/Mew233/pairwise / process_sanger2022

Function process_sanger2022

pairwise/prepare_data.py:66–83  ·  view source on GitHub ↗
()

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64
65 #create a dummy synergy dataframe
66 def process_customized():
67 # drugcomb = process_drugcomb()
68 # # drugcomb_colon = drugcomb[drugcomb['tissue_name'] == 'haematopoietic_and_lymphoid']
69 # drugcomb_colon = drugcomb.drop_duplicates(subset=['drug1', 'drug2'])
70
71 # # crc_exp = pd.read_csv(os.path.join(DATA_DIR, 'cell_line_data','Customized','crc_%s.csv' % "exp"),sep=',')
72 # # crc_exp = pd.read_csv(os.path.join(DATA_DIR, 'cell_line_data','Customized','tcga_DLBC_%s.csv' % "exp"),sep=',')
73 # crc_exp = pd.read_csv(os.path.join(DATA_DIR, 'cell_line_data','Customized','orginal_columbia_DLBC_%s_20221014.csv' % "exp"),sep=',')
74 # # crc_exp = pd.read_csv(os.path.join(DATA_DIR, 'cell_line_data','Customized','lstaudt_DLBC_%s.csv' % "exp"),sep=',')
75 # summary_data = pd.DataFrame(columns=['drug1','drug2','cell','tissue_name','score'])
76 # cell_list = list(crc_exp.columns)
77 # for crc_cell in cell_list: #0:255, 255:
78 # drugcomb_colon['cell'] = crc_cell
79 # drugcomb_colon['score'] = 0
80 # summary_data = summary_data.append(drugcomb_colon, ignore_index=True)
81
82 # summary_data = summary_data.drop_duplicates(subset=['drug1','drug2','cell','tissue_name','score'])
83
84
85 # for dcdb
86 dcdb_tmd8 = pd.read_csv(os.path.join(DATA_DIR, 'synergy_data','Customized','dcdb_tmd8.csv'),sep=',').iloc[:,1:]

Callers

nothing calls this directly

Calls 2

split_itFunction · 0.85
process_drugcombFunction · 0.85

Tested by

no test coverage detected