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That is, first we create a list of lists (``lst``), and then we used ``map()`` to apply
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the ``make_dds`` function to all items in the list. The collapsing of
@@ -260,6 +260,24 @@ adds some extra convenience when working with lists of dds objects, including
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the detection of parallelization as set up in the config object. See the help
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for ``lcdbwf::make_results()`` for more details.
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By default, if no test argument is specified in the parameters for
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``lcdbwf::make_dds`` found here in `examples 1-4, <https://github.com/lcdb/lcdb-wf/blob/LRT/workflows/rnaseq/downstream/rnaseq.Rmd#L164-L187>`_
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the Wald test is performed. When ``lcdbwf::make_results`` processes a Wald test dds object, it
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detects the Wald test and expects a ``contrast`` or ``coef`` argument to specify which
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p-values and log2FoldChange values to report.
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DESeq2 also supports the nBinomLRT (LRT). `Example 5 <https://github.com/lcdb/lcdb-wf/blob/LRT/workflows/rnaseq/downstream/rnaseq.Rmd#L189-L194>`_
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demonstrates how to create a dds object with LRT data. Since the LRT tests
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the removal of one or more terms from the design formula, a single
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log2FoldChange column doesn't reflect the test's complexity. DESeq2's results
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object is optimized for the Wald test, and when storing LRT results, it
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maintains consistency in datastructure by choosing a single pair-wise comparison for
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log2FoldChange values. To avoid confusion, ***we set all log2FoldChange values to
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0 for LRT results***.
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For more details, see the DESeq2 documentation:
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`DESeq2 Likelihood Ratio Test <https://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#i-ran-a-likelihood-ratio-test-but-results-only-gives-me-one-comparison>`_.
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.. _rules:
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To take advantage of this infrastructure, we put each of those contrasts into
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