countRelevantEnrichments: Count Relevant Enrichments

In vertesy/Seurat.utils: Seurat.utils - utility functions for Seurat

Count Relevant Enrichments

Description

This function counts the number of relevantly expressed genes from a differential gene expression table. It considers genes to be relevant if they fall under a maximum p-value cutoff and are above a minimum log2 fold change cutoff. The function reports the number of enriched and depleted genes.

Usage

countRelevantEnrichments(
  df,
  pval_col = "p_val_adj",
  logfc_col = "avg_log2FC",
  pval_cutoff = 0.01,
  logfc_cutoff = 1
)

Arguments

df	Data frame containing the gene expression data.
pval_col	Character. Name of the column containing the adjusted p-values. Default: "p_val_adj".
logfc_col	Character. Name of the column containing the log2 fold change values. Default: "avg_log2FC".
pval_cutoff	Numeric. The maximum adjusted p-value to consider a gene relevant. Default: 1e-2.
logfc_cutoff	Numeric. The minimum log2 fold change to consider a gene relevant. Default: 1.

Value

A list with the counts of enriched and depleted genes.

Examples

df <- data.frame(
  p_val_adj = c(0.001, 0.02, 0.03, 0.0001),
  avg_log2FC = c(1.5, -2, 0.5, 2)
)
countRelevantEnrichments(df)

vertesy/Seurat.utils documentation built on Dec. 4, 2024, 5:20 p.m.