Spaces:
Sleeping
Sleeping
| import pandas as pd | |
| def clean_data(input_set): | |
| data = pd.DataFrame() | |
| try: | |
| if ',' in input_set: | |
| input_set = [i.strip() for i in input_set.split(',')] | |
| for i in input_set: | |
| data = data.append(pd.Series([j.strip() for j in i.split('-')]), ignore_index=True) | |
| data.columns = ['uniprotID', 'wt', 'pos', 'mut'] | |
| elif '\t' in input_set: | |
| input_set = [i.strip() for i in input_set.split('\t')] | |
| for i in input_set: | |
| data = data.append(pd.Series([j.strip() for j in i.split('-')]), ignore_index=True) | |
| data.columns = ['uniprotID', 'wt', 'pos', 'mut'] | |
| elif '-' in input_set: | |
| data = data.append(pd.Series([j.strip() for j in input_set.split('-')]), ignore_index=True) | |
| data.columns = ['uniprotID', 'wt', 'pos', 'mut'] | |
| elif '.txt' in input_set: | |
| data = pd.read_csv(input_set, sep='\t', names=['uniprotID', 'wt', 'pos', 'mut']) | |
| data = data[['uniprotID', 'wt', 'pos', 'mut']] | |
| # Exclude termination codons, synonymous mutations and any non-standard residues such as Sec, 4 or 6. | |
| aa_list = ['A', 'R', 'N', 'D', 'C', 'E', 'Q', 'G', 'H', 'I', 'L', 'K', 'M', 'F', 'P', 'S', 'T', 'W', 'Y', 'V'] | |
| data.wt = data.wt.str.strip() | |
| data.mut = data.mut.str.strip() | |
| data = data[data.wt.isin(aa_list)] | |
| data = data[data.mut.isin(aa_list)] | |
| for i in data.index: | |
| data.at[i, 'datapoint'] = data.at[i, 'uniprotID'] + data.at[i, 'wt'] + str(data.at[i, 'pos']) + data.at[i, 'mut'] | |
| data = data.astype(str) | |
| return data | |
| except: | |
| ValueError | |
| print('Please check the input format.') | |