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R6 class representing a phenotyper

Source: R/phenotype.R
phenotyper.Rd

phenotyper object is used to phenotype populations

Public fields

name

[character] name of the phenotyper

plotCost

[numeric] cost for phenotyping one plot

traits

[list] of phenotyped traits

mu

[numeric] vector of the mean for each trait

ve

[numeric] vector of the environmental variance sigma^2 for each trait

Methods

Public methods

Method new()

Create a new phenotyper object.

Usage

phenotyper$new(
  name,
  traits,
  plotCost = 1,
  mu = 0,
  ve = NULL,
  he = NULL,
  pop = NULL
)

Arguments

name

[character] name of the phenotyper

traits

[trait or list] of phenotyped traits

plotCost

[numeric] cost for phenotyping one plot

mu

[numeric] vector of the mean for each trait

ve

[numeric] (if he not provided) vector of the environmental variance sigma^2 for each trait

he

[numeric] (if ve not provided) vector of the target heredity for each trait

pop

[population] (if ve not provided) population used for the target heredity calculation (see:population)

Returns

A new `phenotyper` object.

Examples

mySpec <- specie$new(nChr = 10,
                    lchr = 10^6,
                    lchrCm = 100,
                    specName = "Geneticae Exempli")
SNPs <- SNPinfo$new(SNPcoord = exampleData$snpCoord,
                   specie = mySpec)
example_pop <- createPop(geno = exampleData$genotypes,
                        SNPinfo = SNPs,
                        popName = "Example population")
myTrait1 <- trait$new(name = "Trait1",
                     qtn = sample(SNPs$SNPcoord$SNPid, 100),
                     qtnEff = rnorm(100, sd = 0.3))
myTrait2 <- trait$new(name = "Trait2",
                     qtn = sample(SNPs$SNPcoord$SNPid, 100),
                     qtnEff = rnorm(100, sd = 0.4))

phenoLab1 <- phenotyper$new(name = "My phenoLab",
                            traits = list(myTrait1, myTrait2),
                            plotCost = 1,
                            mu = c(100, 50),
                            ve = NULL,
                            he = c(0.4, 0.55),
                            pop = example_pop)

phenoLab2 <- phenotyper$new(name = "My phenoLab",
                           traits = list(myTrait1, myTrait2),
                           plotCost = 2,
                           mu = c(100, 50),
                           ve = c(9, 7),
                           he = NULL,
                           pop = NULL)

Method print()

Display informations about the object

Usage

phenotyper$print()

Method trial()

Phenotype a given population

Usage

phenotyper$trial(pop, rep = 1, offset = 0)

Arguments

pop

[population class] population (see: population)

rep

[numeric] number of replication for each individuals

offset

[numeric] offset added to the phenotypic calculation results

Details

phenotypic values for individual i repetition j is calculated as follow: $$y_{ij} = \mu + g_i + e_{ij} + offset$$ $$e_{ij} \sim N(0, \sigma_e^2)$$ where g_i is the genetic value of the individual i

Examples


pheno1 <- phenoLab1$trial(example_pop, rep = 4, offset = c(3, 5))
pheno1$cost
summary(pheno1$data)

pheno2 <- phenoLab2$trial(example_pop, rep = 3, offset = c(-5, 0))
pheno2$cost
summary(pheno2$data)

pheno3 <- phenoLab2$trial(example_pop,
                          rep = round(runif(example_pop$nInd, 1, 3)),
                          offset = c(-5, 0))
pheno3$cost
summary(pheno3$data)

Method he()

Calculate the heritability of a given population

Usage

phenotyper$he(pop)

Arguments

pop

[population] the population

Returns

named numeric vector of the calculated heritability of the population for each trait

Examples

phenoLab1$he(example_pop)
phenoLab2$he(example_pop)

Method clone()

The objects of this class are cloneable with this method.

Usage

phenotyper$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples


## ------------------------------------------------
## Method `phenotyper$new`
## ------------------------------------------------

mySpec <- specie$new(nChr = 10,
                    lchr = 10^6,
                    lchrCm = 100,
                    specName = "Geneticae Exempli")
#> A new species has emerged: Geneticae Exempli !
#> 
SNPs <- SNPinfo$new(SNPcoord = exampleData$snpCoord,
                   specie = mySpec)
example_pop <- createPop(geno = exampleData$genotypes,
                        SNPinfo = SNPs,
                        popName = "Example population")
#> Create population: Initialisation...
#> Create population: Create individuals...
#> 
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#> Create population: Create population object...
#> Create population: Add individuals...
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#> A new population created: Example population !
myTrait1 <- trait$new(name = "Trait1",
                     qtn = sample(SNPs$SNPcoord$SNPid, 100),
                     qtnEff = rnorm(100, sd = 0.3))
myTrait2 <- trait$new(name = "Trait2",
                     qtn = sample(SNPs$SNPcoord$SNPid, 100),
                     qtnEff = rnorm(100, sd = 0.4))

phenoLab1 <- phenotyper$new(name = "My phenoLab",
                            traits = list(myTrait1, myTrait2),
                            plotCost = 1,
                            mu = c(100, 50),
                            ve = NULL,
                            he = c(0.4, 0.55),
                            pop = example_pop)

phenoLab2 <- phenotyper$new(name = "My phenoLab",
                           traits = list(myTrait1, myTrait2),
                           plotCost = 2,
                           mu = c(100, 50),
                           ve = c(9, 7),
                           he = NULL,
                           pop = NULL)


## ------------------------------------------------
## Method `phenotyper$trial`
## ------------------------------------------------


pheno1 <- phenoLab1$trial(example_pop, rep = 4, offset = c(3, 5))
pheno1$cost
#> [1] 400
summary(pheno1$data)
#>      ind                Trait1           Trait2           rep      
#>  Length:400         Min.   : 90.67   Min.   :44.16   Min.   :1.00  
#>  Class :character   1st Qu.: 99.84   1st Qu.:54.01   1st Qu.:1.75  
#>  Mode  :character   Median :102.36   Median :57.25   Median :2.50  
#>                     Mean   :102.13   Mean   :57.15   Mean   :2.50  
#>                     3rd Qu.:104.27   3rd Qu.:60.29   3rd Qu.:3.25  
#>                     Max.   :112.28   Max.   :72.22   Max.   :4.00  
#>   phenotyper       
#>  Length:400        
#>  Class :character  
#>  Mode  :character  
#>                    
#>                    
#>                    

pheno2 <- phenoLab2$trial(example_pop, rep = 3, offset = c(-5, 0))
pheno2$cost
#> [1] 600
summary(pheno2$data)
#>      ind                Trait1           Trait2           rep   
#>  Length:300         Min.   : 79.62   Min.   :39.81   Min.   :1  
#>  Class :character   1st Qu.: 91.25   1st Qu.:49.25   1st Qu.:1  
#>  Mode  :character   Median : 93.88   Median :51.81   Median :2  
#>                     Mean   : 94.01   Mean   :52.20   Mean   :2  
#>                     3rd Qu.: 96.68   3rd Qu.:55.12   3rd Qu.:3  
#>                     Max.   :105.12   Max.   :66.52   Max.   :3  
#>   phenotyper       
#>  Length:300        
#>  Class :character  
#>  Mode  :character  
#>                    
#>                    
#>                    

pheno3 <- phenoLab2$trial(example_pop,
                          rep = round(runif(example_pop$nInd, 1, 3)),
                          offset = c(-5, 0))
pheno3$cost
#> [1] 392
summary(pheno3$data)
#>      ind                Trait1           Trait2           rep       
#>  Length:196         Min.   : 84.44   Min.   :38.87   Min.   :1.000  
#>  Class :character   1st Qu.: 91.49   1st Qu.:49.20   1st Qu.:1.000  
#>  Mode  :character   Median : 94.13   Median :52.77   Median :1.000  
#>                     Mean   : 94.12   Mean   :52.59   Mean   :1.607  
#>                     3rd Qu.: 96.57   3rd Qu.:55.81   3rd Qu.:2.000  
#>                     Max.   :104.31   Max.   :65.37   Max.   :3.000  
#>   phenotyper       
#>  Length:196        
#>  Class :character  
#>  Mode  :character  
#>                    
#>                    
#>                    

## ------------------------------------------------
## Method `phenotyper$he`
## ------------------------------------------------

phenoLab1$he(example_pop)
#> Trait1 Trait2 
#>   0.40   0.55 
phenoLab2$he(example_pop)
#>    Trait1    Trait2 
#> 0.3396647 0.6412943