Bayesian local false discovery rate for sparse count data with application to the discovery of hotspots in protein domains

DOI10.1214/21-AOAS1551zbMath1498.62214MaRDI QIDQ2170401

Dohwan Park, Ilia Rattsev, Maricel G. Kann, Iris Ivy M. Gauran, Junyong Park, Thomas A. Peterson

Publication date: 5 September 2022

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

zbMATH Keywords

protein domainsBayesian local false discovery ratesparse count datazero-inflated generalized Poisson

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Paired and multiple comparisons; multiple testing (62J15)

Cites Work

• Overall objective priors
• A Bayesian analysis of zero-inflated generalized Poisson model
• Bayesian nonparametric multiple testing
• A Bayesian nonparametric multiple testing procedure for comparing several treatments against a control
• An exploration of aspects of Bayesian multiple testing
• Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data
• Empirical Bayes Analysis of a Microarray Experiment
• Bayesian Models for Gene Expression With DNA Microarray Data
• Optimal Sample Size for Multiple Testing
• Generalized Poisson Distribution: the Property of Mixture of Poisson and Comparison with Negative Binomial Distribution
• Detecting differential gene expression with a semiparametric hierarchical mixture method

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