Loading bin/lib/reports.py +33 −8 Original line number Diff line number Diff line Loading @@ -129,10 +129,22 @@ class Reports: # Create dataframe from csv file for each file and save to a list dt_frag_i = pd.read_csv(dt_frag_list[i], sep='\t', header=None, names=['Size','Occurrences']) frag_base_i = os.path.basename(dt_frag_list[i]) sample_id = frag_base_i.split(".")[0] sample_id_split = sample_id.rsplit("_", 1) rep_i = sample_id_split[1] group_i = sample_id_split[0] # split txt files on dots sample_id_list = frag_base_i.split(".") # join list on the elements of the sample id separator = "" sample_id = separator.join(sample_id_list[0:-2]) # split sample id on underscores sample_id_split_list = sample_id.split("_") # take first element of this list for group id group_i = separator.join(sample_id_split_list[0:-1]) # take last element of this list for replicate number rep_i = sample_id_split_list[-1] # Create long forms of fragment histograms dt_frag_i_long = np.repeat(dt_frag_i['Size'].values, dt_frag_i['Occurrences'].values) Loading Loading @@ -203,10 +215,23 @@ class Reports: for i in list(range(len(seacr_bed_list))): seacr_bed_i = pd.read_csv(seacr_bed_list[i], sep='\t', header=None, usecols=[0,1,2,3,4], names=['chrom','start','end','total_signal','max_signal']) bed_base_i = os.path.basename(seacr_bed_list[i]) sample_id = bed_base_i.split(".")[0] sample_id_split = sample_id.rsplit("_", 1) rep_i = sample_id_split[1] group_i = sample_id_split[0] # split bed files on dots bed_id_list = bed_base_i.split(".") # join list on the elements of the sample id separator = "" sample_id = separator.join(bed_id_list[0:-4]) # split sample id on underscores sample_id_split_list = sample_id.split("_") # take first element of this list for group id group_i = separator.join(sample_id_split_list[0:-1]) # take last element fo this list for replicate number rep_i = sample_id_split_list[-1] seacr_bed_i['group'] = np.repeat(group_i, seacr_bed_i.shape[0]) seacr_bed_i['replicate'] = np.repeat(rep_i, seacr_bed_i.shape[0]) Loading tests/test_samplesheet_check.yml +7 −0 Original line number Diff line number Diff line Loading @@ -70,3 +70,10 @@ - samplesheet_M_M files: - path: results/pipeline_info/samplesheet.valid.csv - name: test_samplesheet_check_group_name_with_dot command: nextflow run main.nf -profile docker,test --input https://raw.githubusercontent.com/nf-core/test-datasets/cutandrun/samplesheet/test-GSE145187-small-dot.csv -c tests/config/nextflow.config tags: - samplesheet_group_dot files: - path: results/pipeline_info/samplesheet.valid.csv No newline at end of file Loading
bin/lib/reports.py +33 −8 Original line number Diff line number Diff line Loading @@ -129,10 +129,22 @@ class Reports: # Create dataframe from csv file for each file and save to a list dt_frag_i = pd.read_csv(dt_frag_list[i], sep='\t', header=None, names=['Size','Occurrences']) frag_base_i = os.path.basename(dt_frag_list[i]) sample_id = frag_base_i.split(".")[0] sample_id_split = sample_id.rsplit("_", 1) rep_i = sample_id_split[1] group_i = sample_id_split[0] # split txt files on dots sample_id_list = frag_base_i.split(".") # join list on the elements of the sample id separator = "" sample_id = separator.join(sample_id_list[0:-2]) # split sample id on underscores sample_id_split_list = sample_id.split("_") # take first element of this list for group id group_i = separator.join(sample_id_split_list[0:-1]) # take last element of this list for replicate number rep_i = sample_id_split_list[-1] # Create long forms of fragment histograms dt_frag_i_long = np.repeat(dt_frag_i['Size'].values, dt_frag_i['Occurrences'].values) Loading Loading @@ -203,10 +215,23 @@ class Reports: for i in list(range(len(seacr_bed_list))): seacr_bed_i = pd.read_csv(seacr_bed_list[i], sep='\t', header=None, usecols=[0,1,2,3,4], names=['chrom','start','end','total_signal','max_signal']) bed_base_i = os.path.basename(seacr_bed_list[i]) sample_id = bed_base_i.split(".")[0] sample_id_split = sample_id.rsplit("_", 1) rep_i = sample_id_split[1] group_i = sample_id_split[0] # split bed files on dots bed_id_list = bed_base_i.split(".") # join list on the elements of the sample id separator = "" sample_id = separator.join(bed_id_list[0:-4]) # split sample id on underscores sample_id_split_list = sample_id.split("_") # take first element of this list for group id group_i = separator.join(sample_id_split_list[0:-1]) # take last element fo this list for replicate number rep_i = sample_id_split_list[-1] seacr_bed_i['group'] = np.repeat(group_i, seacr_bed_i.shape[0]) seacr_bed_i['replicate'] = np.repeat(rep_i, seacr_bed_i.shape[0]) Loading
tests/test_samplesheet_check.yml +7 −0 Original line number Diff line number Diff line Loading @@ -70,3 +70,10 @@ - samplesheet_M_M files: - path: results/pipeline_info/samplesheet.valid.csv - name: test_samplesheet_check_group_name_with_dot command: nextflow run main.nf -profile docker,test --input https://raw.githubusercontent.com/nf-core/test-datasets/cutandrun/samplesheet/test-GSE145187-small-dot.csv -c tests/config/nextflow.config tags: - samplesheet_group_dot files: - path: results/pipeline_info/samplesheet.valid.csv No newline at end of file
