Mercurial > repos > greg > draw_amr_matrix
changeset 3:7d7884f2d921 draft
Uploaded
| author | greg |
|---|---|
| date | Fri, 10 Feb 2023 20:04:31 +0000 |
| parents | 9fcc1ffd7526 |
| children | 33a0ea992043 |
| files | draw_amr_matrix.py |
| diffstat | 1 files changed, 6 insertions(+), 2 deletions(-) [+] |
line wrap: on
line diff
--- a/draw_amr_matrix.py Fri Feb 10 17:27:33 2023 +0000 +++ b/draw_amr_matrix.py Fri Feb 10 20:04:31 2023 +0000 @@ -62,7 +62,8 @@ # The call_amr_mutations Galaxy tool will currently produce this VarScan VCF file, but we need a sample that # will produce a populated file. After we find one, we'll need to figure out how to implement this loop # https://github.com/appliedbinf/pima_md/blob/main/pima.py#L2925 in a Galaxy tool so that the VarScan VCF - # file will be converted to the TSV amr_mutations_file that thsi tool expects. + # file will be converted to the TSV amr_mutations_file that thsi tool expects. + amr_mutations = pandas.DataFrame() # Roll up potentially resistance conferring mutations. for mutation_region, mutation_hits in amr_mutations.iteritems(): for mutation_idx, mutation_hit in mutation_hits.iterrows(): @@ -74,7 +75,10 @@ # within the workflow to receive the amr_deletions_file here, although it is currently # always empty... # Roll up deletions that might confer resistance. - amr_deletions = pandas.read_csv(filepath_or_buffer=amr_deletions_file, sep='\t', header=None) + try: + amr_deletions = pandas.read_csv(filepath_or_buffer=amr_deletions_file, sep='\t', header=None) + except Exception: + amr_deletions = pandas.DataFrame() if amr_deletions.shape[0] > 0: amr_deletions.columns = ['contig', 'start', 'stop', 'name', 'type', 'drug', 'note'] amr_deletions = amr_deletions.loc[amr_deletions['type'].isin(['large-deletion', 'any']), :]