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Gimme maelstrom #869
Gimme maelstrom #869
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…ence into gimme_maelstrom
…ence into gimme_maelstrom
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Unless I'm mistaken, at least the dense_samples()
addition is needed to make it robust.
counts = pd.read_table(snakemake.input[0], comment="#", index_col=0) | ||
samples = pd.read_table(StringIO(snakemake.params.samples), sep="\s+") | ||
breps = snakemake.params.breps | ||
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This will parse the samples file the same way (if the descriptive_name
column is sparse, it will use replicate/sample names):
from seq2science.utils import dense_samples
samples = dense_samples(samples, config)
…ence into gimme_maelstrom
…nce into gimme_maelstrom
…ence into gimme_maelstrom
What problem is the PR solving / What's new?
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