A two-stage empirical Bayes method for identifying differentially expressed genes

DOI10.1016/j.csda.2005.07.020zbMath1445.62269OpenAlexW2073613588MaRDI QIDQ959437

Kam-Wah Tsui, Yuan Ji, KyungMann Kim

Publication date: 11 December 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2005.07.020

zbMATH Keywords

conjugate priorsfalse discovery ratemicroarraysmoment matchingabundance grouptoxicogenomics

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10) Empirical decision procedures; empirical Bayes procedures (62C12)

Uses Software

• mclust
• EBarrays
• sma

Cites Work

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• Estimating the dimension of a model
• MCLUST: Software for model-based cluster analysis
• Significance analysis of microarrays applied to the ionizing radiation response
• Identification of Differentially Expressed Genes in High-Density Oligonucleotide Arrays Accounting for the Quantification Limits of the Technology
• Empirical Bayes Analysis of a Microarray Experiment
• Bayesian Models for Gene Expression With DNA Microarray Data
• Detecting differential gene expression with a semiparametric hierarchical mixture method

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