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Plot heat maps with genotype ranking

Source: R/wsmp.R
plot.wsmp.Rd

Plot heat maps with genotype ranking in two ways.

Usage

# S3 method for 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.

Value

An object of class gg.

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.

Author

Tiago Olivoto tiagoolivoto@gmail.com

Examples

# \donttest{
library(metan)
model <- waasb(data_ge2,
               env = ENV,
               gen = GEN,
               rep = REP,
               resp = PH) %>%
         wsmp()
#> Evaluating trait PH |============================================| 100% 00:00:01 

#> Method: REML/BLUP
#> Random effects: GEN, GEN:ENV
#> Fixed effects: ENV, REP(ENV)
#> Denominador DF: Satterthwaite's method
#> ---------------------------------------------------------------------------
#> P-values for Likelihood Ratio Test of the analyzed traits
#> ---------------------------------------------------------------------------
#>     model       PH
#>  COMPLETE       NA
#>       GEN 9.39e-01
#>   GEN:ENV 1.09e-13
#> ---------------------------------------------------------------------------
#> All variables with significant (p < 0.05) genotype-vs-environment interaction
#> Ranks considering 0 for GY and 100 for WAASB |                   | 2% 00:00:00 
Ranks considering 0 for GY and 100 for WAASB |=                  | 3% 00:00:00 
Ranks considering 0 for GY and 100 for WAASB |=                  | 5% 00:00:00 
Ranks considering 5 for GY and 95 for WAASB |=                   | 6% 00:00:00 
Ranks considering 5 for GY and 95 for WAASB |==                  | 8% 00:00:00 
Ranks considering 5 for GY and 95 for WAASB |==                  | 10% 00:00:00 
Ranks considering 10 for GY and 90 for WAASB |==                 | 11% 00:00:01 
Ranks considering 10 for GY and 90 for WAASB |==                 | 13% 00:00:01 
Ranks considering 10 for GY and 90 for WAASB |===                | 14% 00:00:01 
Ranks considering 15 for GY and 85 for WAASB |===                | 16% 00:00:01 
Ranks considering 15 for GY and 85 for WAASB |===                | 17% 00:00:01 
Ranks considering 15 for GY and 85 for WAASB |====               | 19% 00:00:01 
Ranks considering 20 for GY and 80 for WAASB |====               | 21% 00:00:02 
Ranks considering 20 for GY and 80 for WAASB |====               | 22% 00:00:02 
Ranks considering 20 for GY and 80 for WAASB |=====              | 24% 00:00:02 
Ranks considering 25 for GY and 75 for WAASB |=====              | 25% 00:00:02 
Ranks considering 25 for GY and 75 for WAASB |=====              | 27% 00:00:02 
Ranks considering 25 for GY and 75 for WAASB |=====              | 29% 00:00:02 
Ranks considering 30 for GY and 70 for WAASB |======             | 30% 00:00:02 
Ranks considering 30 for GY and 70 for WAASB |======             | 32% 00:00:03 
Ranks considering 30 for GY and 70 for WAASB |======             | 33% 00:00:03 
Ranks considering 35 for GY and 65 for WAASB |=======            | 35% 00:00:03 
Ranks considering 35 for GY and 65 for WAASB |=======            | 37% 00:00:03 
Ranks considering 35 for GY and 65 for WAASB |=======            | 38% 00:00:03 
Ranks considering 40 for GY and 60 for WAASB |========           | 40% 00:00:03 
Ranks considering 40 for GY and 60 for WAASB |========           | 41% 00:00:03 
Ranks considering 40 for GY and 60 for WAASB |========           | 43% 00:00:04 
Ranks considering 45 for GY and 55 for WAASB |========           | 44% 00:00:04 
Ranks considering 45 for GY and 55 for WAASB |=========          | 46% 00:00:04 
Ranks considering 45 for GY and 55 for WAASB |=========          | 48% 00:00:04 
Ranks considering 50 for GY and 50 for WAASB |=========          | 49% 00:00:04 
Ranks considering 50 for GY and 50 for WAASB |==========         | 51% 00:00:04 
Ranks considering 50 for GY and 50 for WAASB |==========         | 52% 00:00:04 
Ranks considering 55 for GY and 45 for WAASB |==========         | 54% 00:00:05 
Ranks considering 55 for GY and 45 for WAASB |===========        | 56% 00:00:05 
Ranks considering 55 for GY and 45 for WAASB |===========        | 57% 00:00:05 
Ranks considering 60 for GY and 40 for WAASB |===========        | 59% 00:00:05 
Ranks considering 60 for GY and 40 for WAASB |===========        | 60% 00:00:05 
Ranks considering 60 for GY and 40 for WAASB |============       | 62% 00:00:05 
Ranks considering 65 for GY and 35 for WAASB |============       | 63% 00:00:05 
Ranks considering 65 for GY and 35 for WAASB |============       | 65% 00:00:06 
Ranks considering 65 for GY and 35 for WAASB |=============      | 67% 00:00:06 
Ranks considering 70 for GY and 30 for WAASB |=============      | 68% 00:00:06 
Ranks considering 70 for GY and 30 for WAASB |=============      | 70% 00:00:06 
Ranks considering 70 for GY and 30 for WAASB |==============     | 71% 00:00:06 
Ranks considering 75 for GY and 25 for WAASB |==============     | 73% 00:00:06 
Ranks considering 75 for GY and 25 for WAASB |==============     | 75% 00:00:06 
Ranks considering 75 for GY and 25 for WAASB |==============     | 76% 00:00:07 
Ranks considering 80 for GY and 20 for WAASB |===============    | 78% 00:00:07 
Ranks considering 80 for GY and 20 for WAASB |===============    | 79% 00:00:07 
Ranks considering 80 for GY and 20 for WAASB |===============    | 81% 00:00:07 
Ranks considering 85 for GY and 15 for WAASB |================   | 83% 00:00:07 
Ranks considering 85 for GY and 15 for WAASB |================   | 84% 00:00:07 
Ranks considering 85 for GY and 15 for WAASB |================   | 86% 00:00:07 
Ranks considering 90 for GY and 10 for WAASB |=================  | 87% 00:00:08 
Ranks considering 90 for GY and 10 for WAASB |=================  | 89% 00:00:08 
Ranks considering 90 for GY and 10 for WAASB |=================  | 90% 00:00:08 
Ranks considering 95 for GY and 5 for WAASB |==================  | 92% 00:00:08 
Ranks considering 95 for GY and 5 for WAASB |=================== | 94% 00:00:08 
Ranks considering 95 for GY and 5 for WAASB |=================== | 95% 00:00:08 
Ranks considering 100 for GY and 0 for WAASB |================== | 97% 00:00:09 
Ranks considering 100 for GY and 0 for WAASB |===================| 98% 00:00:09 
Ranks considering 100 for GY and 0 for WAASB |===================| 100% 00:00:09 


p1 <- plot(model)
#> Warning: Vectorized input to `element_text()` is not officially supported.
#> ℹ Results may be unexpected or may change in future versions of ggplot2.
p2 <- plot(model, type = 2)
#> Warning: Vectorized input to `element_text()` is not officially supported.
#> ℹ Results may be unexpected or may change in future versions of ggplot2.
arrange_ggplot(p1, p2, ncol = 1)

# }