get_feature_ranks: Get feature ranking vector from differential abundance...

In AlexanderKirchmair/datamisc: Various functions for data handling

Get feature ranking vector from differential abundance testing results

Description

Calculate ranking values to sort features from most upregulated to most downregulated for GSEA

Usage

get_feature_ranks(
  data,
  rank_by = "stat",
  rank_type = "",
  id_col = NULL,
  direction_by = NULL,
  ...
)

Arguments

rank_type

Examples

df <- data.frame(id = rgenes(n = 100), stat = rnorm(100), mean = runif(100))
df[1:50,-1] <- df[51:100,-1] # make duplicates
df |> get_feature_ranks(rank_by = c("stat", "mean"), rank_type = c("", ""), id_col="id")

dds <- DESeq2::makeExampleDESeqDataSet(n = 10000, interceptMean = c(2,5))
res <- dds |> runDESeq2(formula = ~ condition, contrasts = list(BvsA = c("condition", "B", "A")))
res$results$BvsA |> get_feature_ranks(rank_by = c("pvalue", "baseMean"), rank_type = c("p", ""), direction_by = "log2FC")

AlexanderKirchmair/datamisc documentation built on June 13, 2025, 5:26 a.m.