feat: added cauris mutations #21
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boasvdp
commented
May 16, 2025
| df_input[["type", "locus_tag", "mutation_name"]] = df_input["BCSQ"].str.split( | ||
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| # split on comma to separate multiple entries on single line | ||
| df_input['BCSQ'] = df_input['BCSQ'].str.split(",") |
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Sometimes bcftools csq outputs multiple aa changes on a single line, separated by a comma. This is now accounted for
boasvdp
commented
May 16, 2025
| # Get number of columns. Ususally 7 or 9 with the second to last containing aa mutation | ||
| # This differs per reference | ||
| nr_col = df_input_long["BCSQ"].str.split("|", expand=True).shape[1] | ||
| aa_mutation_col = nr_col -2 |
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Assumption: aa mutation is listed in second to last column. This holds true for both reference genome annotations we use, but should be checked when implementing new reference genome annotations
boasvdp
commented
May 16, 2025
| @@ -190,7 +204,7 @@ def filter_for_known_mutations( | |||
| Dataframe with only known mutations | |||
| """ | |||
| df_known_mutations = df_resistance_with_impact_renamed[ | |||
| df_resistance_with_impact_renamed["impact"].notnull() | |||
| df_resistance_with_impact_renamed["impact"].notnull() | df_resistance_with_impact_renamed["drug"].notnull() | |||
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Also output a mutations as "known" if only the drug column has info, but impact column is empty
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