auto_process_ngs.commands.analyse_barcodes_cmd
- auto_process_ngs.commands.analyse_barcodes_cmd.analyse_barcodes(ap, unaligned_dir=None, lanes=None, mismatches=None, cutoff=None, barcode_analysis_dir=None, sample_sheet=None, name=None, runner=None, force=False)
Analyse the barcode sequences for Fastqs for each specified lane
Run ‘analyse_barcodes.py’ for one or more lanes, to analyse the barcode index sequences in each lane.
- Parameters:
ap (AutoProcessor) – autoprocessor pointing to the analysis directory to create Fastqs for
unaligned_dir (str) – if set then use this as the output directory for bcl-to-fastq conversion. Default is ‘bcl2fastq’ (unless an alternative is already specified in the config file)
lanes (list) – (optional) specify a list of lane numbers to use in the processing; lanes not in the list will be excluded (default is to include all lanes)
mismatches (int) – (optional) maximum number of mismatches to consider when grouping similar barcodes; default is to determine it automatically
cutoff (float) – (optional) exclude barcodes with a smaller fraction of associated reads than specified cutoff from reporting (e.g. ‘0.001’ excludes barcodes with < 0.1% of reads); default is to include all barcodes
barcode_analysis_dir (str) – (optional) explicitly specify the subdirectory to use for barcode analysis. Counts will be written to and read from the ‘counts’ subdirectory of this directory (defaults to ‘barcode_analysis’)
sample_sheet (str) – if set then use this as the input samplesheet to check barcode sequences against (by default will use the sample sheet defined in the parameter file for the run)
name (str) – (optional) identifier for output directory (if ‘barcode_analysis_dir’ not explicitly set) and report title
runner (JobRunner) – (optional) specify a non-default job runner to use for barcode analysis
force (bool) – if True then forces regeneration of any existing counts (default is to reuse existing counts)