BOPA: A Bayesian hierarchical model for outlier expression detection
type: Item
instance of: scholarly article
title: BOPA: A Bayesian hierarchical model for outlier expression detection
zbMATH Open document ID: 1255.62065
author: Zhaoping Hong
author: Heng Lian
published in: Computational Statistics and Data Analysis
publication date: 2012-12-30T00:00:00Z
full work available at URL: http://hdl.handle.net/10356/49053
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 62P10
Mathematics Subject Classification ID: 92C50
zbMATH DE Number: 6119811
zbMATH Keywords: cancer outlier profile analysis
zbMATH Keywords: false discovery rate
zbMATH Keywords: Markov chain Monte Carlo
zbMATH Keywords: microarrays
describes a project that uses: boa
describes a project that uses: gaga
MaRDI profile type: Publication
OpenAlex ID: W2162808038
cites work: A Bayesian Mixture Model for Differential Gene Expression
cites work: Large-Scale Simultaneous Hypothesis Testing
cites work: Inference from iterative simulation using multiple sequences
cites work: Bayesian Robust Inference for Differential Gene Expression in Microarrays with Multiple Samples
cites work: Bayesian Models for Gene Expression With DNA Microarray Data
cites work: Bayesian testing of many hypotheses \(\times \) many genes: a study of sleep apnea
cites work: Bayesian Modeling of Differential Gene Expression
cites work: Detecting differential gene expression with a semiparametric hierarchical mixture method
cites work: Gaga: a parsimonious and flexible model for differential expression analysis
cites work: Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
cites work: Statistical significance for genomewide studies
cites work: Outlier sums for differential gene expression analysis
cites work: Cancer outlier differential gene expression detection
DOI: 10.1016/J.CSDA.2012.05.003
description: scientific article; zbMATH DE number 6119811