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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/LimmaAnalyze.R
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\name{limma_analyze}
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\alias{limma_analyze}
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\title{Differential Gene Expression Analysis using limma and voom}
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\usage{
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limma_analyze(
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  tumor_file,
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  normal_file,
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  output_file,
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  logFC_threshold = 2.5,
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  p_value_threshold = 0.01
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)
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}
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\arguments{
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\item{tumor_file}{Path to the tumor data file (RDS format).}
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\item{normal_file}{Path to the normal data file (RDS format).}
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\item{output_file}{Path to save the output DEG data (RDS format).}
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\item{logFC_threshold}{Threshold for log fold change for marking up/down-regulated genes.}
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\item{p_value_threshold}{Threshold for p-value for filtering significant genes.}
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}
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\value{
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A data frame of differential expression results.
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}
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\description{
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This function performs differential gene expression analysis using the 'limma' package with voom normalization.
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It reads tumor and normal expression data, merges them, filters low-expressed genes,
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normalizes the data, performs limma analysis, and outputs the results along with information
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on gene expression changes.
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}
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\examples{
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# Define file paths for tumor and normal data from the data folder
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tumor_file <- system.file("extdata",
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                          "removebatch_SKCM_Skin_TCGA_exp_tumor_test.rds",
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                          package = "TransProR")
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normal_file <- system.file("extdata",
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                           "removebatch_SKCM_Skin_Normal_TCGA_GTEX_count_test.rds",
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                           package = "TransProR")
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output_file <- file.path(tempdir(), "DEG_limma_voom.rds")
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DEG_limma_voom <- limma_analyze(
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  tumor_file = tumor_file,
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  normal_file = normal_file,
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  output_file = output_file,
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  logFC_threshold = 2.5,
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  p_value_threshold = 0.01
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)
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# View the top 5 rows of the result
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head(DEG_limma_voom, 5)
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}
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\references{
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limma:Linear Models for Microarray and RNA-Seq Data User’s Guide.
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For more information, visit the page:
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https://www.bioconductor.org/packages/release/bioc/vignettes/limma/inst/doc/usersguide.pdf
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}