BOPA: A Bayesian hierarchical model for outlier expression detection

DOI10.1016/j.csda.2012.05.003zbMath1255.62065OpenAlexW2162808038MaRDI QIDQ1927193

Zhaoping Hong, Heng Lian

Publication date: 30 December 2012

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

Full work available at URL: http://hdl.handle.net/10356/49053

zbMATH Keywords

Markov chain Monte Carlofalse discovery ratemicroarrayscancer outlier profile analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Medical applications (general) (92C50)

Uses Software

• boa
• gaga

Cites Work

• Gaga: a parsimonious and flexible model for differential expression analysis
• Bayesian testing of many hypotheses \(\times \) many genes: a study of sleep apnea
• Inference from iterative simulation using multiple sequences
• Outlier sums for differential gene expression analysis
• Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
• Bayesian Models for Gene Expression With DNA Microarray Data
• Cancer outlier differential gene expression detection
• Statistical significance for genomewide studies
• Bayesian Modeling of Differential Gene Expression
• Bayesian Robust Inference for Differential Gene Expression in Microarrays with Multiple Samples
• Large-Scale Simultaneous Hypothesis Testing
• Detecting differential gene expression with a semiparametric hierarchical mixture method
• A Bayesian Mixture Model for Differential Gene Expression

This page was built for publication: BOPA: A Bayesian hierarchical model for outlier expression detection