Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
- PMID: 34605806
- DOI: 10.3791/62528
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Abstract
RNA sequencing (RNA-seq) is one of the most widely used technologies in transcriptomics as it can reveal the relationship between the genetic alteration and complex biological processes and has great value in diagnostics, prognostics, and therapeutics of tumors. Differential analysis of RNA-seq data is crucial to identify aberrant transcriptions, and limma, EdgeR and DESeq2 are efficient tools for differential analysis. However, RNA-seq differential analysis requires certain skills with R language and the ability to choose an appropriate method, which is lacking in the curriculum of medical education. Herein, we provide the detailed protocol to identify differentially expressed genes (DEGs) between cholangiocarcinoma (CHOL) and normal tissues through limma, DESeq2 and EdgeR, respectively, and the results are shown in volcano plots and Venn diagrams. The three protocols of limma, DESeq2 and EdgeR are similar but have different steps among the processes of the analysis. For example, a linear model is used for statistics in limma, while the negative binomial distribution is used in edgeR and DESeq2. Additionally, the normalized RNA-seq count data is necessary for EdgeR and limma but is not necessary for DESeq2. Here, we provide a detailed protocol for three differential analysis methods: limma, EdgeR and DESeq2. The results of the three methods are partly overlapping. All three methods have their own advantages, and the choice of method only depends on the data.
Similar articles
-
Robust identification of differentially expressed genes from RNA-seq data.Genomics. 2020 Mar;112(2):2000-2010. doi: 10.1016/j.ygeno.2019.11.012. Epub 2019 Nov 20. Genomics. 2020. PMID: 31756426
-
SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data.PLoS One. 2016 Jun 9;11(6):e0157022. doi: 10.1371/journal.pone.0157022. eCollection 2016. PLoS One. 2016. PMID: 27280887 Free PMC article.
-
Bacterial Differential Expression Analysis Methods.Methods Mol Biol. 2020;2096:89-112. doi: 10.1007/978-1-0716-0195-2_8. Methods Mol Biol. 2020. PMID: 32720149
-
RNA-Seq differential expression analysis: An extended review and a software tool.PLoS One. 2017 Dec 21;12(12):e0190152. doi: 10.1371/journal.pone.0190152. eCollection 2017. PLoS One. 2017. PMID: 29267363 Free PMC article. Review.
-
Interpretation of differential gene expression results of RNA-seq data: review and integration.Brief Bioinform. 2019 Nov 27;20(6):2044-2054. doi: 10.1093/bib/bby067. Brief Bioinform. 2019. PMID: 30099484 Free PMC article. Review.
Cited by
-
Multi-omics characterization of type 2 diabetes mellitus-induced gastroenteropathy in the db/db mouse model.Front Cell Dev Biol. 2024 Aug 15;12:1417255. doi: 10.3389/fcell.2024.1417255. eCollection 2024. Front Cell Dev Biol. 2024. PMID: 39211388 Free PMC article.
-
Construction of a mitophagy-related prognostic signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma.Heliyon. 2024 Jul 31;10(15):e35305. doi: 10.1016/j.heliyon.2024.e35305. eCollection 2024 Aug 15. Heliyon. 2024. PMID: 39170577 Free PMC article.
-
The role of NPC2 gene in glioma was investigated based on bioinformatics analysis.Sci Rep. 2024 Aug 19;14(1):19134. doi: 10.1038/s41598-024-70221-z. Sci Rep. 2024. PMID: 39160329 Free PMC article.
-
Neutrophils exposed to a cholesterol metabolite secrete extracellular vesicles that promote epithelial-mesenchymal transition and stemness in breast cancer cells.bioRxiv [Preprint]. 2024 Aug 2:2024.08.02.606061. doi: 10.1101/2024.08.02.606061. bioRxiv. 2024. PMID: 39131340 Free PMC article. Preprint.
-
Insights into the Gene Expression Profile of Classical Hodgkin Lymphoma: A Study towards Discovery of Novel Therapeutic Targets.Molecules. 2024 Jul 25;29(15):3476. doi: 10.3390/molecules29153476. Molecules. 2024. PMID: 39124881 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources