filter_diff_genes: Filter Differentially Expressed Genes

In TransProR: Analysis and Visualization of Multi-Omics Data

Filter Differentially Expressed Genes

Description

This function filters a data frame to identify genes with significant differential expression based on specified thresholds for p-values and log fold change. It allows for flexible input of column names for p-values and log fold change.

Usage

filter_diff_genes(
  data,
  p_val_col = "adj.P.Val",
  log_fc_col = "logFC",
  p_val_threshold = 0.05,
  log_fc_threshold = 1
)

Arguments

data	A data frame containing gene expression data.
p_val_col	Character string indicating the column name for p-values. Default is "adj.P.Val".
log_fc_col	Character string indicating the column name for log fold change. Default is "logFC".
p_val_threshold	Numeric threshold for filtering p-values. Default is 0.05.
log_fc_threshold	Numeric threshold for filtering log fold change. Default is 1.0.

Value

A data frame with genes filtered by the specified criteria.

Examples

# Create a sample data frame with p-values and log fold changes
sample_data <- data.frame(
  adj.P.Val = c(0.03, 0.06, 0.02, 0.07),
  logFC = c(1.5, 0.8, -1.2, 1.1),
  gene = c("Gene1", "Gene2", "Gene3", "Gene4")
)

# Use the filter_diff_genes function to filter significant genes
filtered_genes <- filter_diff_genes(sample_data)
print(filtered_genes)

TransProR documentation built on April 4, 2025, 3:16 a.m.