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Top markers per group from wilcoxauc results

top_markers.Rd

Filters and ranks the long-form output of wilcoxauc() to give the most distinguishing features per group. The filter arguments combine multiplicatively, then the top n features per group are kept by descending auc and pivoted into wide form. Counterpart to top_markers_dds() for DESeq2-based pseudobulk results.

Usage

top_markers(
  res,
  n = 10,
  auc_min = 0,
  pval_max = 1,
  padj_max = 1,
  pct_in_min = 0,
  pct_out_max = 100
)

Arguments

res

Long-form results table from wilcoxauc().

n

Number of top markers to return per group. Default 10.

auc_min

Drop features with auc < auc_min. Default 0 (no filter); set to 0.5 to keep only features that are positive markers (more highly expressed in-group than out).

pval_max

Drop features with raw pval > pval_max. Default 1.

padj_max

Drop features with adjusted padj > padj_max. Default 1.

pct_in_min

Minimum percent (0-100) of in-group observations with non-zero feature value. Default 0.

pct_out_max

Maximum percent (0-100) of out-of-group observations with non-zero feature value. Default 100.

Value

tibble in wide form: a rank column (1..n) and one column per group containing the feature name of the top-ranked marker at that rank. Cells are NA for groups with fewer than n features that pass the filters.

See also

wilcoxauc(), top_markers_dds()

Examples

set.seed(42)
exprs <- matrix(rpois(25 * 150, lambda = 2), nrow = 25,
                dimnames = list(paste0("G", 1:25), NULL))
y <- rep(c("A", "B", "C"), each = 50)

res <- wilcoxauc(exprs, y)

## top 10 markers per group, restricted to nominally significant,
## up-regulated features (auc > 0.5 means in-group > out-of-group).
top_markers(res, n = 10, auc_min = 0.5, pval_max = 0.05)
#> # A tibble: 2 × 2
#>    rank C    
#>   <int> <chr>
#> 1     1 G25  
#> 2     2 G5