analysis_deps_limma: Differential expression analysis using limma.

In ecnuzdd/PhosMap: A Comprehensive R Package For Analyzing Quantitative Phosphoproteomics Data

Differential expression analysis using limma.

Description

Differential expression analysis using limma.

Usage

analysis_deps_limma(
  expr_data_frame,
  group,
  comparison_factor,
  log2_label = FALSE,
  adjust_method = "BH"
)

Arguments

expr_data_frame	A data frame containing ID and quantification values.
group	A factor for representing experimental groups.
comparison_factor	A vector for comparison groups.
log2_label	A boolean value for representing whether the value is logarithmic or not, the default is FALSE.
adjust_method	Method used to adjust the p-values for multiple testing. See p.adjust for the complete list of options, the default is "BH"

Value

A list containing results from limma analysis.

Author(s)

Dongdong Zhan and Mengsha Tong

References

Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression \ analyses for RNA-sequencing and microarray studies. Nucleic Acids Research 43(7), e47.

Examples

## The process needs to load data from PhosMap datasets stored into FTP server and perform large computation.
## It may take a few minutes.
if(FALSE){
ftp_url <- "ftp://111.198.139.72:4000/pub/PhosMap_datasets/function_demo_data/analysis_deps_limma.RData"
load_data <- load_data_with_ftp(ftp_url, 'RData')
writeBin(load_data, "analysis_deps_limma.RData")
load("analysis_deps_limma.RData")

limma_results_df <- analysis_deps_limma(
  expr_data_frame, group, group_levels,
  log2_label = FALSE, adjust_method = 'none'
)
head(limma_results_df)

}

ecnuzdd/PhosMap documentation built on Dec. 7, 2022, 4:09 a.m.