FC_P: Calculate Fold Change and p-values for differential...

In LipidomicsR: Elegant Tools for Processing and Visualization of Lipidomics Data

Calculate Fold Change and p-values for differential expression analysis

Description

This function calculates the log2 fold change (FC) and p-values for differential expression analysis between two groups of data.

Usage

FC_P(compare1, compare2, p.adj = FALSE, method = "fdr")

Arguments

compare1	A matrix or data frame representing the first group of data.
compare2	A matrix or data frame representing the second group of data.
p.adj	Logical. Should p-values be adjusted for multiple testing?
method	The method to use for p-value adjustment. Options: 'fdr', 'bonferroni', 'holm', etc.

Value

A data frame containing the log2 fold change and -log10 transformed p-values for each row (e.g., genes, features) in the input data.

Examples

compare1 <- matrix(rnorm(100), ncol = 10)
compare2 <- matrix(rnorm(100), ncol = 10)
result <- FC_P(compare1, compare2, p.adj = TRUE)

LipidomicsR documentation built on May 29, 2024, 8:59 a.m.