# plot.wsmp: Plot heat maps with genotype ranking In metan: Multi Environment Trials Analysis

## Description

Plot heat maps with genotype ranking in two ways.

## Usage

 1 2 ## S3 method for class 'wsmp' plot(x, var = 1, type = 1, y.lab = NULL, x.lab = NULL, size.lab = 12, ...) 

## Arguments

 x An object returned by the function wsmp. var The variable to plot. Defaults to var = 1 the first variable of x. type 1 = Heat map Ranks: this graphic shows the genotype ranking considering the WAASB index estimated with different numbers of Principal Components; 2 = Heat map WAASY-GY ratio: this graphic shows the genotype ranking considering the different combinations in the WAASB/GY ratio. y.lab The label of y axis. Default is 'Genotypes'. x.lab The label of x axis. Default is 'Number of axes'. size.lab The size of the labels. ... Currently not used.

## Details

The first type of heatmap shows the genotype ranking depending on the number of principal component axis used for estimating the WAASB index. The second type of heatmap shows the genotype ranking depending on the WAASB/GY ratio. The ranks obtained with a ratio of 100/0 considers exclusively the stability for the genotype ranking. On the other hand, a ratio of 0/100 considers exclusively the productivity for the genotype ranking. Four clusters of genotypes are shown by label colors (red) unproductive and unstable genotypes; (blue) productive, but unstable genotypes; (black) stable, but unproductive genotypes; and (green), productive and stable genotypes.

## Value

An object of class gg.

## Author(s)

Tiago Olivoto tiagoolivoto@gmail.com

## Examples

  1 2 3 4 5 6 7 8 9 10 11 library(metan) model <- waasb(data_ge2, env = ENV, gen = GEN, rep = REP, resp = PH) %>% wsmp() p1 <- plot(model) p2 <- plot(model, type = 2) arrange_ggplot(p1, p2, ncol = 1) 

metan documentation built on Nov. 10, 2021, 9:11 a.m.