| pseudobulk_one_vs_all | R Documentation |
For each level of contrast_var, fits a DESeq2 model where that
level is the foreground and every other level is pooled as the
background. Useful for marker-style differential expression: the
return is one set of (log2FoldChange, padj) per gene per group,
giving a quick view of what's elevated in each group relative to
the rest.
pseudobulk_one_vs_all(
dge_formula,
counts_df,
meta_data,
contrast_var,
vals_test,
collapse_background,
verbose
)
dge_formula |
One-sided formula such as |
counts_df |
Feature-by-pseudobulk integer count matrix. Rows
are features; columns must align with rows of |
meta_data |
data.frame of pseudobulk metadata. One row per
pseudobulk; should contain only the variables used in
|
contrast_var |
Name of the contrast column in |
vals_test |
Character vector of contrast levels to test. If
|
collapse_background |
Used only when |
verbose |
Logical. Print progress messages. Default |
Most users should call pseudobulk_deseq2() with
mode = "one_vs_all" rather than this function directly; the
wrapper handles formula parsing, gene-count filtering, and
dispatch. See the pseudobulk vignette for a worked example.
data.frame of DESeq2 results with columns group,
feature, baseMean, log2FoldChange, lfcSE, stat,
pvalue, padj. Sorted by stat descending within each group.
pseudobulk_deseq2(), pseudobulk_pairwise(),
pseudobulk_within(), top_markers_dds()
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