ArticleBMC bioinformatics2013
Differential expression analysis for paired RNA-Seq data.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Early Transcriptomic Signatures of Immune Response Modulation Following Antiretroviral Therapy in HIV-Infected Patients.International journal of molecular sciences · 2025Article
- Frequency and duration of sensory flicker control transcriptional profiles in 5xFAD mice.APL bioengineering · 2025Article
- A survey of biclustering and clustering methods in clustering different types of single-cell RNA sequencing data.Briefings in functional genomics · 2025Article
- Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.International journal of molecular sciences · 2024Article
- Transcriptome profile of pecan scab resistant and susceptible trees from a pecan provenance collection.BMC genomics · 2024Article
- Transcriptomic Analysis Reveals Potential Gene Regulatory Networks Under Cold Stress of Loquat (Frontiers in plant science · 2022Article
- The Autoimmune Protocol Diet Modifies Intestinal RNA Expression in Inflammatory Bowel Disease.Crohn's & colitis 360 · 2019Article
- PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effects.Bioinformatics (Oxford, England) · 2019Article
- A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation.Metabolites · 2018Article
- Biomarker detection and categorization in ribonucleic acid sequencing meta-analysis using Bayesian hierarchical models.Journal of the Royal Statistical Society. Series C, Applied statistics · 2017Article
- Article
- RNA-seq Data: Challenges in and Recommendations for Experimental Design and Analysis.Current protocols in human genetics · 2014Article
- Integrative RNA-seq and microarray data analysis reveals GC content and gene length biases in the psoriasis transcriptome.Physiological genomics · 2014Article
- Identification of genes critical for resistance to infection by West Nile virus using RNA-Seq analysis.Viruses · 2013Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundRNA-Seq technology measures the transcript abundance by generating sequence reads and counting their frequencies across different biological conditions. To identify differentially expressed genes between two conditions, it is important to consider the experimental design as well as the distributional property of the data. In many RNA-Seq studies, the expression data are obtained as multiple pairs, e.g., pre- vs. post-treatment samples from the same individual. We seek to incorporate paired structure into analysis.
resultsWe present a Bayesian hierarchical mixture model for RNA-Seq data to separately account for the variability within and between individuals from a paired data structure. The method assumes a Poisson distribution for the data mixed with a gamma distribution to account variability between pairs. The effect of differential expression is modeled by two-component mixture model. The performance of this approach is examined by simulated and real data.
conclusionsIn this setting, our proposed model provides higher sensitivity than existing methods to detect differential expression. Application to real RNA-Seq data demonstrates the usefulness of this method for detecting expression alteration for genes with low average expression levels or shorter transcript length.
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