add aggregate_spike_count to reports.py #955
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add a new function, aggregate_spike_count, to reports.py to produce a matrix of spike-in counts per-sample from an array of per-sample spike-in count files
yesimon
reviewed
May 29, 2019
reports.py
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| spike_in_sample_counts[spike][s] = count | ||
| #outf.write('\t'.join([s, spike, count]) + '\n') | ||
| outf.write("\t".join(["spike-in"]+samples_seen)+"\n") | ||
| for spike in spike_in_sample_counts.keys(): |
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Sorted IDs or OrderedDict?
yesimon
reviewed
May 29, 2019
reports.py
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| def parser_aggregate_spike_count(parser=argparse.ArgumentParser()): | ||
| parser.add_argument('inDir', help='Input spike count directory.') |
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metavar these so variables can avoid camelcasing?
sort spike-ins listed in aggregated report; also metavar positional args to avoid camel case in signature of called function. path used as base for glob is now passed through realpath to standardize the path a bit more and allow paths specified with or without trailing slashes (realpath removes them if present)
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This adds a new function,
aggregate_spike_count, toreports.pyto produce a matrix of spike-in counts per-sample from a directory containing array of per-sample spike-in count files. This is in contrast toconsolidate_spike_countwhich simply concatenates the count files (without extraneous columns).