ArticleComputational and structural biotechnology journal2021
Robustness of differential gene expression analysis of RNA-seq.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.
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Who cites it
42 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Gene-Based Clustering Identifies QSOX1 and IL1RAP as Biomarkers of Metabolic Dysfunction-Associated Steatotic Liver Disease.Liver international : official journal of the International Association for the Study of the Liver · 2026Article
- Biological pathways related to mirna-125a-5p in behavioral variant of frontotemporal dementia.Molecular biology reports · 2026Article
- Transcriptomic analysis of fatty acid and cannabinoid synthases in an S1 cannabis progeny segregating for propyl cannabinoid biosynthesis.Plant molecular biology · 2026Article
- Tool choice matters: Evaluating edgeR vs. DESeq2 for sensitivity, robustness, and cross-study performance.PloS one · 2026Article
- SubNExT: Towards accurate, efficient and robust gene expression classification for breast cancer subtyping.Computational and structural biotechnology journal · 2026Article
- Machine Learning Models for Cancer Research: A Narrative Review of Bulk RNA-Seq Applications.International journal of molecular sciences · 2025Review
- From bulk RNA sequencing to spatial transcriptomics: a comparative review of differential gene expression analysis methods.Human genomics · 2025Review
- Computational identification and validation of non-coding rna biomarkers in gastrointestinal cancer.Functional & integrative genomics · 2025Review
- Novel methods for temporally varying gene identification in longitudinal studies reveal bleeding and clotting pathway activation caused by blood draws.Briefings in bioinformatics · 2025Article
- Genome-wide transcriptome differences associated with perceived discrimination in an urban, community-dwelling middle-aged cohort.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025Article
- Prioritization of candidate genes regulating the dwarfness in rice by integration of whole-genome and transcriptome analyses.Functional & integrative genomics · 2025Article
- Multiple programmed cell death patterns predict the prognosis and drug sensitivity in gastric cancer.Frontiers in immunology · 2025Article
- Comparative gene expression analysis ofPeerJ · 2025Article
- Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review.Computational and structural biotechnology journal · 2024Review
- A benchmark of RNA-seq data normalization methods for transcriptome mapping on human genome-scale metabolic networks.NPJ systems biology and applications · 2024Article
- Comparative Transcriptome Analysis of Bovine, Porcine, and Sheep Muscle Using Interpretable Machine Learning Models.Animals : an open access journal from MDPI · 2024Article
- Gibberellin 2-oxidase 1(CsGA2ox1) involved gibberellin biosynthesis regulates sprouting time in camellia sinensis.BMC plant biology · 2024Article
- De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide.Frontiers in zoology · 2024Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA-sequencing (RNA-seq) is a relatively new technology that lacks standardisation. RNA-seq can be used for Differential Gene Expression (DGE) analysis, however, no consensus exists as to which methodology ensures robust and reproducible results. Indeed, it is broadly acknowledged that DGE methods provide disparate results. Despite obstacles, RNA-seq assays are in advanced development for clinical use but further optimisation will be needed. Herein, five DGE models (DESeq2, voom + limma, edgeR, EBSeq, NOISeq) for gene-level detection were investigated for robustness to sequencing alterations using a controlled analysis of fixed count matrices. Two breast cancer datasets were analysed with full and reduced sample sizes. DGE model robustness was compared between filtering regimes and for different expression levels (high, low) using unbiased metrics. Test sensitivity estimated as relative False Discovery Rate (FDR), concordance between model outputs and comparisons of a 'population' of slopes of relative FDRs across different library sizes, generated using linear regressions, were examined. Patterns of relative DGE model robustness proved dataset-agnostic and reliable for drawing conclusions when sample sizes were sufficiently large. Overall, the non-parametric method NOISeq was the most robust followed by edgeR, voom, EBSeq and DESeq2. Our rigorous appraisal provides information for method selection for molecular diagnostics. Metrics may prove useful towards improving the standardisation of RNA-seq for precision medicine.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.