The R package switchgrassGWAS provides functions for genome-wide association analysis on the Panicum virgatum diversity (pvdiv) panel. It’s associated with this paper.
You can install the development version from GitHub from within R:
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("Alice-MacQueen/switchgrassGWAS")This will give you access to the package functions, example and previously published phenotypes, and the currently available information about the genotypes in the switchgrass diversity panel.
Some switchgrassGWAS functions require the installation of additional packages.
These packages can be installed from within R with:
install.packages("bigsnpr")
install.packages("mashr")
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
install.packages("curl")
BiocManager::install(c("GenomicFeatures", "VariantAnnotation"))The switchgrass (Panicum virgatum) diversity panel, the pvdiv panel, is being grown at many common gardens across the United States and Mexico. Many researchers are measuring phenotypes on this panel to understand the genes and genetic regions affecting these phenotypes.
This package provides the code for fast, less memory intensive genome-wide association (GWAS) using bigsnpr. It also provides functions to link diversity panel phenotypic data with publicly available SNP data, to prepare GWAS results plots using ggplot, and to prepare multiple univariate GWAS results for use in the downstream application mash.
For a start, have a look at the code example provided for genome-wide
association,
and the arguments for the function
pvdiv_standard_gwas.
Download the SNP data here.
Look at the metadata for genotypes in the diversity panel, and the publicly available phenotypes.
The HTML documentation for the development version is available on Github.
If you find the switchgrassGWAS package or any of the source code in this repository useful for your work, please cite:
Lovell, J.T., MacQueen, A.H., Mamidi, S. et al. Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass. Nature (2021). https://doi.org/10.1038/s41586-020-03127-1