fill.design: Filling the design of an experiment

Description

The fill.design function allows the user to fill the missing rows and ranges from an experiment to run specific designs or apply a post blocking. The data frame requires the presence of 2 numeric columns indicating the x and y coordinates, here denominated rows and ranges. This can be effectively used for multi environment trials by using the `by` argument where you specify the column that indicates the environments.

Usage

fill.design(x,rows="ROW",ranges="RANGE",by, extra)

Arguments

a dataframe with 2 obligatory columns; rows and ranges which can have different names and can be matched with the next arguments.

rows

the name of the numeric column that indicates one direction in the field.

ranges

the name of the numeric column that indicates the other direction in the field.

optional argument to indicate the name of the column of the dataframe x that indicates the environments so the field is filled by environment.

extra

name of the extra columns to be filled in the dataset based. This are filled based on the rows, ranges information.

Value

$xnew: a new dataframe identical to the one provided but with missing rows and ranges filled in.

References

Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744

Examples

Run this code

# NOT RUN {
  
####=========================================####
#### For CRAN time limitations most lines in the 
#### examples are silenced with one '#' mark, 
#### remove them and run the examples using
#### command + shift + C |OR| control + shift + C
####=========================================####
data(CPdata)
CPpheno <- CPdata$pheno#[,-c(1:4)]
CPgeno <- CPdata$geno
#### look at the data
head(CPpheno)
#### fill the design
gg <- fill.design(x=CPpheno, rows="Row",ranges="Col")
head(gg)

# }