ArticleBMC genomics2014
Bootstrap-based differential gene expression analysis for RNA-Seq data with and without replicates.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Development and comparison of evaluation metrics for batch correction reveals performance differences.Bioinformatics advances · 2026Article
- Machine Learning Models for Cancer Research: A Narrative Review of Bulk RNA-Seq Applications.International journal of molecular sciences · 2025Review
- Intratumoral Microbiota Correlates with AP-2 Expression: A Pan-Cancer Map with Cohort-Specific Prognostic and Molecular Footprints.International journal of molecular sciences · 2025Article
- Tree-based differential testing using inferential uncertainty for RNA-seq.Genome research · 2025Article
- Tree-based differential testing using inferential uncertainty for RNA-Seq.bioRxiv : the preprint server for biology · 2025Article
- Genomic reproducibility in the bioinformatics era.Genome biology · 2024Review
- HuR controls glutaminase RNA metabolism.Nature communications · 2024Article
- Molecular landscapes of glioblastoma cell lines revealed a group of patients that do not benefit fromFrontiers in neuroscience · 2023Article
- A comparison of strategies for generating artificial replicates in RNA-seq experiments.Scientific reports · 2022Article
- Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Pipeline for Analyzing Activity of Metabolic Pathways in Planktonic Communities Using Metatranscriptomic Data.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Transcriptome Analysis ofMicroorganisms · 2021Article
- Compression of quantification uncertainty for scRNA-seq counts.Bioinformatics (Oxford, England) · 2021Article
- Disruption of exon-bridging interactions between the minor and major spliceosomes results in alternative splicing around minor introns.Nucleic acids research · 2021Article
- Transcriptomic analysis reveals key transcription factors associated to drought tolerance in a wild papaya (Carica papaya) genotype.PloS one · 2021Article
- Statistical Modeling of High Dimensional Counts.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.Frontiers in immunology · 2021Article
- Transcriptome profiling of raspberry (Heliyon · 2020Article
- Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data.Bioinformatics (Oxford, England) · 2020Article
- Detecting, Categorizing, and Correcting Coverage Anomalies of RNA-Seq Quantification.Cell systems · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A major application of RNA-Seq is to perform differential gene expression analysis. Many tools exist to analyze differentially expressed genes in the presence of biological replicates. Frequently, however, RNA-Seq experiments have no or very few biological replicates and development of methods for detecting differentially expressed genes in these scenarios is still an active research area. In this paper we introduce a novel method, called IsoDE, for differential gene expression analysis based on bootstrapping. We compared IsoDE against four existing methods (Fisher’s exact test, GFOLD, edgeR and Cuffdiff) on RNA-Seq datasets generated using three different sequencing technologies, both with and without replicates. Experiments on MAQC RNA-Seq datasets without replicates show that IsoDE has consistently high accuracy as defined by the qPCR ground truth, frequently higher than that of the compared methods, particularly for low coverage data and at lower fold change thresholds. In experiments on RNA-Seq datasets with up to 7 replicates, IsoDE has also achieved high accuracy. Furthermore, unlike GFOLD and edgeR, IsoDE accuracy varies smoothly with the number of replicates, and is relatively uniform across the entire range of gene expression levels. The proposed non-parametric method based on bootstrapping has practical running time, and achieves robust performance over a broad range of technologies, number of replicates, sequencing depths, and minimum fold change thresholds.
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