README.md

In PopVar: Genomic Breeding Tools: Genetic Variance Prediction and Cross-Validation

PopVar

Introduction

To make progress in breeding, populations should have a favorable mean and high genetic variance (Bernardo 2010). These two parameters can be combined into a single measure called the usefulness criterion (Schnell and Utz 1975), visualized in Figure 1.

Ideally, breeders would identify the set of parent combinations that, when realized in a cross, would give rise to populations meeting these requirements. PopVar is a package that uses phenotypic and genomewide marker data on a set of candidate parents to predict the mean, genetic variance, and superior progeny mean in bi-parental or multi-parental populations. Thre package also contains functionality for performing cross-validation to determine the suitability of different statistical models. More details are available in Mohammadi, Tiede, and Smith (2015). A dataset think_barley is included for reference and examples.

Installation

You can install the released version of PopVar from CRAN with:

install.packages("PopVar")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("UMN-BarleyOatSilphium/PopVar")

Functions

Below is a description of the functions provided in PopVar:

| Function | Description | | --------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | pop.predict | Uses simulations to make predictions in recombinant inbred line populations; can internally perform cross-validation for model selections; can be quite slow. | | pop.predict2 | Uses deterministic equations to make predictions in populations of complete or partial selfing and with or without the induction of doubled haploids; is much faster than pop.predict; does not perform cross-validation or model selection internally. | | pop_predict2 | Has the same functionality as pop.predict2, but accepts genomewide marker data in a simpler matrix format. | | x.val | Performs cross-validation to estimate model performance. | | mppop.predict | Uses deterministic equations to make predictions in 2- or 4-way populations of complete or partial selfing and with or without the induction of doubled haploids; does not perform cross-validation or model selection internally. | | mpop_predict2 | Has the same functionality as mppop.predict, but accepts genomewide marker data in a simpler matrix format. |

Examples

Examples are outlined in the package vignette.

References

Bernardo, Rex. 2010. *Breeding for Quantitative Traits in Plants*. 2nd ed. Woodbury, Minnesota: Stemma Press.

Mohammadi, Mohsen, Tyler Tiede, and Kevin P. Smith. 2015. “PopVar: A Genome-Wide Procedure for Predicting Genetic Variance and Correlated Response in Biparental Breeding Populations.” *Crop Science* 55 (5): 2068–77. .

Schnell, F. W., and H. F. Utz. 1975. “F1-leistung und elternwahl euphyder züchtung von selbstbefruchtern.” In *Bericht über Die Arbeitstagung Der Vereinigung Österreichischer Pflanzenzüchter*, 243–48. Gumpenstein, Austria: BAL Gumpenstein.

PopVar documentation built on Feb. 8, 2021, 1:06 a.m.