deg_filter

This function filters out genes based on their expression change status.
It returns the names of genes which are not "stable".

A tool for comprehensive transcriptomic data analysis, with a focus on transcript-level data preprocessing, expression profiling, differential expression analysis, and functional enrichment. It enables researchers to identify key biological processes, disease biomarkers, and gene regulatory mechanisms. 'TransProR' is aimed at researchers and bioinformaticians working with RNA-Seq data, providing an intuitive framework for in-depth analysis and visualization of transcriptomic datasets. The package includes comprehensive documentation and usage examples to guide users through the entire analysis pipeline. The differential expression analysis methods incorporated in the package include 'limma' (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>; Smyth, 2005, <doi:10.1007/0-387-29362-0_23>), 'edgeR' (Robinson et al., 2010, <doi:10.1093/bioinformatics/btp616>), 'DESeq2' (Love et al., 2014, <doi:10.1186/s13059-014-0550-8>), and Wilcoxon tests (Li et al., 2022, <doi:10.1186/s13059-022-02648-4>), providing flexible and robust approaches to RNA-Seq data analysis. For more information, refer to the package vignettes and related publications.

Dongyue Yu

TransProR

Analysis and Visualization of Multi-Omics Data

deg_filter function

<dl><dt>df</dt>
<dd>A data frame containing gene expression data.</dd></dl>

Arguments

Function to Filter Differentially Expressed Genes (DEGs) — deg_filter

<dl>

<dt>df</dt>
<dd>A data frame containing gene expression data.</dd>

</dl>

deg_filter: Function to Filter Differentially Expressed Genes (DEGs)

Description

Usage

Value

Arguments

Examples