Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

12-2015

Journal or Book Title

Journal of Agricultural, Biological, and Environmental Statistics

Volume

20

Issue

4

First Page

598

Last Page

613

DOI

10.1007/s13253-015-0232-3

Abstract

The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental units and uses negative binomial distributions to allow for overdispersion in count responses for split-plot experimental units. Variations in gene length and base content, as well as differences in sequencing intensity across experimental units, are also accounted for. Hierarchical modeling with thoughtful parameterization and prior specification allows for borrowing of information across genes to improve estimation of dispersion parameters, genotype effects, treatment effects, and interaction effects of primary interest.

Comments

This is a manuscript of an article published as Lithio, Andrew, and Dan Nettleton. "Hierarchical modeling and differential expression analysis for RNA-seq experiments with inbred and hybrid genotypes." Journal of agricultural, biological, and environmental statistics 20, no. 4 (2015): 598-613. doi: 10.1007/s13253-015-0232-3. Posted with permission.

Copyright Owner

International Biometric Society

Language

en

File Format

application/pdf

Published Version

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