Jeffrey Endelman
Plant breeders typically use multi-environment datasets that are unbalanced with respect to individuals over time and often within year as well. Experimental designs and the best models for micro-environmental variation may also vary with environment, defined as a location x year combination. These complexities can be handled efficiently with a two-stage analysis, in which best linear unbiased estimates (BLUEs) of genotypic value are computed for each environment in Stage 1 and then used as the response variable in Stage 2. To fully utilize the data, however, the variance-covariance matrix of the estimates from Stage 1 should be included in Stage 2 (Piepho et al. 2012; Damesa et al. 2017), which is not possible with most software packages for genomics-assisted breeding.
R package StageWise was developed to provide a simple interface for genomic selection and GWAS based on a fully efficient, two-stage analysis (Endelman 2023). Each phenotypic record is associated with a single genotype id, which is suitable for clonal and inbred lines but not hybrid crops. The ASReml-R package is used for variance component estimation, which requires a license from VSN International.
Software development has been supported by USDA Hatch Project 1013047 and the USDA National Institute of Food and Agriculture (NIFA) Award 2020-51181-32156. The potato datasets were generated with support from NIFA Awards 2016-34141-25707 and 2019-34141-30284, Potatoes USA, the Wisconsin Potato and Vegetable Growers Association, and the University of Wisconsin-Madison.
To install and load the package:
install.packages("devtools")
devtools::install_github("jendelman/StageWise", build_vignettes=FALSE)
library(StageWise)There are three vignettes in the package:
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Vignette 1 illustrates analysis of a single trait with a homogeneous GxE model (same genetic correlation between all environments).
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Vignette 2 illustrates analysis of a single trait with heterogeneous GxE covariance, which is often needed with diverse locations.
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Vignette 3 illustrates the analysis of correlated traits under a homogeneous GxE model.
For a complete specification of package functions, consult the reference manual.