97 lines
4 KiB
Python
Executable file
97 lines
4 KiB
Python
Executable file
#!/usr/bin/env python3
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import pandas as pd
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DEBUG = False
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#%%
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#def find_missense(df, ref_allele1, alt_allele0):
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def find_missense(df, ref_allele_column, alt_allele_column, n_diff_colname = 'n_diff', tot_diff_colname = 'tot_diff', ref_a_colname = 'ref_allele', alt_a_colname = 'alt_allele'):
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"""Find mismatches in pairwise comparison of strings b/w col_a and col_b
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Case insensitive, converts strings to uppercase before comparison
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@df: df containing columns to compare
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@type: pandas df
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@ref_allele_column: column containing ref allele str
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@type: str (converts to uppercase)
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@alt_allele_column: column containing alt_allele str
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@type: str (converts to uppercase)
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@n_diff_colname: user defined colname for no. of char diff b/w ref_allele_str and alt_allele_str
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@type: str
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@tot_diff_colname: user defined colname abs diff to indicate if strings are of equal length
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@type: str
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@ref_a_colname: user defined colname containing extracted referece allele
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@type: str
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@alt_a_colname: user defined colname containing extracted alt allele
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@type: str
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returns df: with 4 added columns. If column names clash, the function column
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name will override original column
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@rtype: pandas df
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"""
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for ind, val in df.iterrows():
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if DEBUG:
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print('index:', ind, 'value:', val
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, '\n============================================================')
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ref_a = val[ref_allele_column].upper()
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alt_a = val[alt_allele_column].upper()
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if DEBUG:
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print('ref_allele_string:', ref_a, 'alt_allele_string:', alt_a)
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difference = sum(1 for e in zip(ref_a, alt_a) if e[0] != e[1])
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df.at[ind, n_diff_colname] = difference # adding column
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tot_difference = difference + abs(len(ref_a) - len(alt_a))
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df.at[ind, tot_diff_colname] = tot_difference # adding column
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if difference != tot_difference:
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print('WARNING: lengths of ref_allele and alt_allele differ at index:', ind
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, '\nNon-missense muts detected')
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# Now finding the mismatched char
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ref_aln = ''
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alt_aln = ''
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if ref_a == alt_a:
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##df.at[ind, 'ref_allele'] = 'no_change' # adding column
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##df.at[ind, 'alt_allele'] = 'no_change' # adding column
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df.at[ind, ref_a_colname] = 'no_change' # adding column
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df.at[ind, alt_a_colname] = 'no_change' # adding column
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elif len(ref_a) == len(alt_a) and len(ref_a) > 0:
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print('ref:', ref_a, 'alt:', alt_a)
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for n in range(len(ref_a)):
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if ref_a[n] != alt_a[n]:
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ref_aln += ref_a[n]
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alt_aln += alt_a[n]
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##df.at[ind, 'ref_allele'] = ref_aln
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##df.at[ind, 'alt_allele'] = alt_aln
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df.at[ind, ref_a_colname] = ref_aln
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df.at[ind, alt_a_colname] = alt_aln
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print('ref:', ref_aln)
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print('alt:', alt_aln)
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else:
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##df.at[ind, 'ref_allele'] = 'ERROR_Not_nsSNP'
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##df.at[ind, 'alt_allele'] = 'ERROR_Not_nsSNP'
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df.at[ind, ref_a_colname] = 'ERROR_Not_nsSNP'
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df.at[ind, alt_a_colname] = 'ERROR_Not_nsSNP'
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return df
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#========================================
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# a representative example
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#eg_df = pd.read_csv('pnca_assoc.txt', sep = '\t', nrows = 10, header = 0, index_col = False)
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#eg_df = pd.DataFrame(eg_df)
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#eg_df = {'chromosome_number': [2288719, 2288766, 2288775, 2288779, 2288827, 1111111, 2222222],
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# 'ref_allele1': ['Tc', 'AG', 'AGCACCCTG', 'CCCTGGTGGCC', 'CACA', 'AA', 'CAT'],
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# 'alt_allele0': ['CC', 'CA', 'GGCACCCTGZ','TCCTGGTGGCCAAD', 'TACA', 'AA', 'TCZ']}
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#def main():
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#find_missense(eg_df, ref_allele1 = 'ref_allele', alt_allele0 = 'alt_allele')
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# find_missense(df = eg_df, ref_allele_column = 'ref_allele1', alt_allele_column = 'alt_allele0')
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# print(eg_df)
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#if __name__ == '__main__':
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# main()
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