From 0b9ecdc880eea6062c8771c7809542cba80211d5 Mon Sep 17 00:00:00 2001 From: iquasere Date: Thu, 23 Nov 2023 11:43:13 +0000 Subject: [PATCH] Minor code formatting --- workflow/scripts/metaproteomics.py | 4 ++-- workflow/scripts/quantification.py | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/workflow/scripts/metaproteomics.py b/workflow/scripts/metaproteomics.py index e568336..f05c897 100644 --- a/workflow/scripts/metaproteomics.py +++ b/workflow/scripts/metaproteomics.py @@ -299,7 +299,7 @@ def select_proteins_for_second_search(self, original_db, output, results_files, output=f'{output}/2nd_search_database.fasta') def run(self): - """ + Path(snakemake.params.output).mkdir(parents=True, exist_ok=True) # 1st database construction self.database_generation( @@ -313,7 +313,7 @@ def run(self): self.generate_parameters_file(f'{snakemake.params.output}/1st_params.par', protein_fdr=100) except: print('An illegal reflective access operation has occurred. But MOSCA can handle it.') - """ + # 2nd database construction proteins_for_second_search = [] for i in range(len(snakemake.params.names)): diff --git a/workflow/scripts/quantification.py b/workflow/scripts/quantification.py index f83c65d..b356e7e 100644 --- a/workflow/scripts/quantification.py +++ b/workflow/scripts/quantification.py @@ -27,8 +27,8 @@ def run(): else: continue if ',' in pexps.loc[i]['Files']: - reads = [f"{snakemake.params.output}/Preprocess/Trimmomatic/quality_trimmed_{pexps.loc[i]['Name']}_{fr}_paired.fq" - for fr in ['forward', 'reverse']] + reads = [(f"{snakemake.params.output}/Preprocess/Trimmomatic/quality_trimmed_{pexps.loc[i]['Name']}_" + f"{fr}_paired.fq") for fr in ['forward', 'reverse']] else: reads = [f"{snakemake.params.output}/Preprocess/Trimmomatic/quality_trimmed_{pexps.loc[i]['Name']}.fq"] perform_alignment( @@ -38,8 +38,8 @@ def run(): f"{snakemake.params.output}/Quantification/{pexps.loc[i]['Name']}.readcounts", reference) # Read the results of alignment and add them to the readcounts result at sample level normalized_by_gene_size = pd.read_csv( - f"{snakemake.params.output}/Quantification/{pexps.loc[i]['Name']}.readcounts.norm", sep='\t', - names=['Gene' if pexps.loc[i]['Data type'] == 'mrna' else 'Contig', pexps.loc[i]['Name']]) + f"{snakemake.params.output}/Quantification/{pexps.loc[i]['Name']}.readcounts.norm", + sep='\t', names=['Gene' if pexps.loc[i]['Data type'] == 'mrna' else 'Contig', pexps.loc[i]['Name']]) if pexps.loc[i]['Data type'] == 'dna': mg_result = pd.merge(mg_result, normalized_by_gene_size, how='outer', on='Contig') else: