Combining assumptions and graphical network into gene expression data analysis

DOI10.1186/s40488-021-00126-zOpenAlexW3181924398WikidataQ114600030 ScholiaQ114600030MaRDI QIDQ2129241

E. O. George, Dale Bowman, Demba Fofana

Publication date: 22 April 2022

Published in: Journal of Statistical Distributions and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/s40488-021-00126-z

zbMATH Keywords

gene expressionBayesian spatial networkmultiple testings

Mathematics Subject Classification ID

Statistical distribution theory (62Exx)

Uses Software

• CARBayes
• HybridMTest

Cites Work

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• Assumption adequacy averaging as a concept for developing more robust methods for differential gene expression analysis
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• A Saturated Model for Analyzing Exchangeable Binary Data: Applications to Clinical and Developmental Toxicity Studies
• Bayesian Analysis of Agricultural Field Experiments

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