2018
DOI: 10.1093/bib/bby067
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Interpretation of differential gene expression results of RNA-seq data: review and integration

Abstract: Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many applications of RNA-seq data analysis. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE resu… Show more

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Cited by 200 publications
(125 citation statements)
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“…RNA sequencing has become an important technique to understand genomic functions ( Hrdlickova et al , 2017 ). The most common application of RNA-seq is for the identification of differentially regulated genes under two or more conditions ( McDermaid et al , 2018 ). In this study, RNA-seq was applied to identify differentially regulated genes in C .…”
Section: Resultsmentioning
confidence: 99%
“…RNA sequencing has become an important technique to understand genomic functions ( Hrdlickova et al , 2017 ). The most common application of RNA-seq is for the identification of differentially regulated genes under two or more conditions ( McDermaid et al , 2018 ). In this study, RNA-seq was applied to identify differentially regulated genes in C .…”
Section: Resultsmentioning
confidence: 99%
“…Analysis of differential gene transcription and normalization of read counts and PCA were performed with R package DESeq2 (v.1.22.2) ( Love et al, 2014 ). Four-way plots were generated with R package vidger (v.1.2.1) ( McDermaid et al, 2019 ).…”
Section: Methodsmentioning
confidence: 99%
“…To identify DEGs in the SREBP-1c KO mice in comparison to in the WT mice, the EdgeR package was chosen since, up to 2018, it has been the most widely used by researchers [16] and has demonstrated better performance in identifying true positives [17] compared to Cuffdiff2 and DESeq. The ExactTest function in the EdgeR package was used to analyze DEGs [18].…”
Section: Identification Of Degs In the Hippocampus Of Srebp-1c Ko Micmentioning
confidence: 99%