pbr

Description

This is the companion R Package to the book Plant Breeding in R. It is primarily used to load all of the packages necessary for completing the tasks outlined in Plant Breeding in R. However, there are some functions that are provided within the package that may be useful.

Installation

You can install this package using the devtools package:

devtools::install_github("neyhartj/pbr")

When you install pbr, a number of other packages are installed. The core set of packages - those that you might need for most analyses - include:

• dplyr, tidyr, readr, for data management and modeling
• ggplot2, for visualization
• lme4, for fitting mixed-effect models
• agridat, for various agricultural experiment data

Additionally, other packages are installed that may be useful for specialized analysis, including those for:

• Managing genetic experiments and QTL mapping

  • qtl, for QTL mapping and simulations
  • rrBLUP, for GWAS and genomic selection

• Statistics:

  • agricolae, for statistical procedures in agriculture research
  • BGLR, for Bayesian linear regression
  • lsmeans, for calculating least-square means

Usage

Loading the pbr package also loads the core set of packages (dplyr, tidyr, readr, ggplot, lme4, agridat):

library(pbr)
#> Loading pbr: dplyr
#> Loading pbr: readr
#> Loading pbr: lme4
#> Loading pbr: agridat

Packages that are not in the core set must be loaded individually using the library() function, for instance:

library(qtl)

Functions

The pbr package includes endogenous functions to support the other packages. Those include

Function	Purpose
dist_env()	Clustering of environments based on phenoypic observations
herit()	Estimating heritability and variance components from fitted model object
herit_boot()	Calculating confidence intervals for heritability based on bootstrapping

Support

Please open an issue for support or to comment.