Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice

Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice

Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad...

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Bibliographic Details
Main Authors: Paul L. Maurizio, Martin T. Ferris, Gregory R. Keele, Darla R. Miller, Ginger D. Shaw, Alan C. Whitmore, Ande West, Clayton R. Morrison, Kelsey E. Noll, Kenneth S. Plante, Adam S. Cockrell, David W. Threadgill, Fernando Pardo-Manuel de Villena, Ralph S. Baric, Mark T. Heise, William Valdar
Format: Article
Language:English
Published: Oxford University Press 2018-02-01
Series:G3: Genes, Genomes, Genetics
Subjects:
treatment response
causal effect
Bayesian mixed model
multiple imputation
multiparental populations
MPP
Online Access:http://g3journal.org/lookup/doi/10.1534/g3.117.300438

Internet

http://g3journal.org/lookup/doi/10.1534/g3.117.300438

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