Bayesian analysis of RNA-Seq data using a family of negative binomial models

DOI10.1214/17-BA1055zbMath1407.62414OpenAlexW2605274789MaRDI QIDQ1631554

Dai Feng, Hui Jiang, Lili Zhao, Wei-Sheng Wu, XuanLong Nguyen

Publication date: 6 December 2018

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ba/1491616976

zbMATH Keywords

Bayesian RNA-seqChinese restaurant table distributiondifferential testexon usagenegative binomial (NB) modeltranscript analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Protein sequences, DNA sequences (92D20)

Uses Software

• Bioconductor
• edgeR
• BaySeq
• ShrinkBayes
• TopHat
• EBSeq
• IUTA
• rSeqDiff
• DESeq2

Cites Work

• The NBP negative binomial model for assessing differential gene expression from RNA-Seq
• Statistical modeling of RNA-Seq data
• Logratio analysis and compositional distance.
• Monte Carlo methods in Bayesian computation
• Fully Bayesian Mixture Model for Differential Gene Expression: Simulations and Model Checks
• Semiparametric Bayesian Inference for Phage Display Data
• Statistical significance for genomewide studies
• Bayesian survival analysis
• Unnamed Item
• Unnamed Item

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