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Pseudobulk DESeq2: one-vs-all contrasts

pseudobulk_one_vs_all.Rd

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.

Usage

pseudobulk_one_vs_all(
  dge_formula,
  counts_df,
  meta_data,
  contrast_var,
  vals_test,
  collapse_background,
  verbose
)

Arguments

dge_formula

One-sided formula such as ~cluster + donor. The first term is treated as the contrast variable in "one_vs_all" and "pairwise" modes, or as the split variable in "within" mode (in which case the second term becomes the contrast variable). Additional terms are kept as covariates in the DESeq2 design.

counts_df

Feature-by-pseudobulk integer count matrix. Rows are features; columns must align with rows of meta_data.

meta_data

data.frame of pseudobulk metadata. One row per pseudobulk; should contain only the variables used in dge_formula.

contrast_var

Name of the contrast column in meta_data (the first term of dge_formula).

vals_test

Character vector of contrast levels to test. If NULL (default), every level of the contrast variable is tested.

collapse_background

Used only when mode = "one_vs_all". If TRUE, background pseudobulks are collapsed across the contrast variable before each DESeq2 fit, which helps when donor representation is unbalanced across clusters. Default TRUE.

verbose

Logical. Print progress messages. Default TRUE.

Value

data.frame of DESeq2 results with columns group, feature, baseMean, log2FoldChange, lfcSE, stat, pvalue, padj. Sorted by stat descending within each group.

Details

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.

See also

pseudobulk_deseq2(), pseudobulk_pairwise(), pseudobulk_within(), top_markers_dds()