heritability_n_blues: Compute heritability and genotypic BLUEs for each selected...

In DeependraD/expdean: Collection of Design and Analysis Functions for Agriculture and Related Fields Data

Description

Compute heritability and genotypic BLUEs for each selected grouping variable adjusting for covariate.

Usage

heritability_n_blues(
  df,
  grouping_var,
  grouping_items_sel,
  dependent_var,
  covariate = NULL,
  genotype_var,
  replication_var
)

Arguments

df	A dataframe or similar object of coercible class.
grouping_var	Column name of the grouping variable such as location or environment of character or factor type.
grouping_items_sel	A character vector of items which are subset of grouping variable selected for obtaining heritability.
dependent_var	Column name of response variable whose heritability estimates are being obtained through model.
covariate	Column name of numeric variable. Adjusted values of dependent variable for this covariate will be used in obtaining estimates.
replication_var	Column name of variable representing replicated records of genotypes/treatments.
genotype	Column name of variable representing genotypes/treatments.

Value

A list

Note

Adapted from 'meta-r' application package

Examples

library(lme4)
library(emmeans)
require(tidyverse)
# load data
df <- expdean::simple_rcbd_df
df <- mutate_at(df, c("Genotype", "Rep"), as.factor)
# check for factor levels
df %>%
  select_if(list(~is.factor(.)|is.character(.))) %>%
  map_int(~length(unique(.x)))
# calculate genetic correlation for locations in absence of other grouping factors while adjusting for covariate
heritability_n_blues(df, grouping_items_sel = c("Buenos Aires", "Beijin", "Karaj"),
                     grouping_var = Location,
                     genotype = Genotype, replication_var = Rep,
                     dependent_var = YLD, covariate = TGW)

DeependraD/expdean documentation built on Nov. 25, 2019, 12:33 a.m.