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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/WilcoxonAnalyze.R
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\name{Wilcoxon_analyze}
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\alias{Wilcoxon_analyze}
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\title{Differential Gene Expression Analysis Using Wilcoxon Rank-Sum Test}
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\usage{
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Wilcoxon_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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  fdr_threshold = 0.05
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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{fdr_threshold}{Threshold for FDR 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 Wilcoxon rank-sum tests.
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It reads tumor and normal expression data, performs TMM normalization using 'edgeR', and uses Wilcoxon rank-sum tests to identify differentially expressed genes.
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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(), "Wilcoxon_rank_sum_testoutRst.rds")
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# Run the Wilcoxon rank sum test
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outRst <- Wilcoxon_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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  fdr_threshold = 0.01
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)
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# View the top 5 rows of the result
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head(outRst, 5)
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}
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\references{
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Li, Y., Ge, X., Peng, F., Li, W., & Li, J. J. (2022). Exaggerated False Positives by Popular
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Differential Expression Methods When Analyzing Human Population Samples. Genome Biology, 23(1), 79.
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DOI: https://doi.org/10.1186/s13059-022-02648-4.
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}