args = parser.parse_args() seq_run = args.run adaIDs = args.adaIDs VERBOSE = args.verbose submit = args.submit threads = args.threads refname = args.reference summary = args.summary use_trimmed = args.trimmed maxreads = args.maxreads subsrate = args.subsrate gapopen = args.gapopen gapextend = args.gapextend # Specify the dataset dataset = load_sequencing_run(seq_run) data_folder = dataset.folder # If the script is called with no adaID, iterate over all samples = dataset.samples if adaIDs is not None: samples = samples.loc[samples.adapter.isin(adaIDs)] if VERBOSE >= 2: print samples.index.tolist() # Iterate over all adaIDs for samplename, sample in samples.iterrows(): adaID = str(sample.adapter) # Submit to the cluster self if requested if submit:
parser.add_argument('--test', action='store_true', help='Include sanity checks on mapped reads (slow)') parser.add_argument('--no-summary', action='store_false', dest='summary', help='Do not save results in a summary file') args = parser.parse_args() seq_run = args.run adaIDs = args.adaIDs VERBOSE = args.verbose maxreads = args.maxreads minisize = args.minisize submit = args.submit include_tests = args.test summary = args.summary dataset = load_sequencing_run(seq_run) data_folder = dataset.folder # Set the number of cycles of the kit (for trimming adapters in short inserts) n_cycles = dataset['cycles'] # If the script is called with no adaID, iterate over all samples = dataset.samples if adaIDs is not None: samples = samples.loc[samples.adapter.isin(adaIDs)] for (samplename, sample) in samples.iterrows(): if str(sample.PCR) == 'nan': if VERBOSE: print samplename+': PCR type not found, skipping' continue