Genotypic Variance

The `gvc` class calculates genotypic variance, phenotypic variance, and broad-sense heritability from replicated data.

Details

The `gvc` class uses methods explained by Burton, G. W. & Devane, E. H. (1953) and Allard, R.W. (2010). It includes methods for calculating genetic variance, phenotypic variance, and heritability.

Public fields

data

A `tibble` containing the data for analysis.

y

The name of the response variable.

x

The name of the covariate (optional).

rep

The name of the replicate factor.

gen

The name of the genotype factor.

env

The name of the environmental factor.

Methods

Public methods

• gvc$new()

• gvc$calculate_gvar()

• gvc$calculate_pvar()

• gvc$calculate_herit()

• gvc$clone()

---

Method new()

Initialize the `gvc` class with the data and variable names.

Usage

gvc$new(.data, .y, .x = NULL, .rep, .gen, .env)

Arguments

.data

A `data.frame` containing the data for analysis.

.y

The response variable.

.x

The covariate (optional).

.rep

The replicate factor.

.gen

The genotype factor.

.env

The environmental factor.

Returns

An instance of the `gvc` class.

---

Method calculate_gvar()

Calculate genetic variance.

Usage

gvc$calculate_gvar()

Returns

A list with the genetic variance (`gvar`).

---

Method calculate_pvar()

Calculate phenotypic variance.

Usage

gvc$calculate_pvar()

Returns

A list with the phenotypic variance (`pvar`).

---

Method calculate_herit()

Calculate broad-sense heritability.

Usage

gvc$calculate_herit()

Returns

A list with the heritability (`h2`).

---

Method clone()

The objects of this class are cloneable with this method.

Usage

gvc$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

df1 <- data.frame(
           Response = c(
                          rnorm(48, mean = 15000, sd = 500)
                        , rnorm(48, mean =  5000, sd = 500)
                        , rnorm(48, mean =  1000, sd = 500)
                       )
        , Rep      = as.factor(rep(1:3, each = 48))
        , Variety  = gl(n = 4, k =  4, length = 144, labels = letters[1:4])
        , Env      = gl(n = 3, k = 16, length = 144, labels = letters[1:3])
        )

# Create an instance of the class
gvc1 <- gvc$new(
           .data = df1
         , .y    = Response
         , .rep  = Rep
         , .gen  = Variety
         , .env  = Env
         )

# Calculate genetic variance (gvar)
gvc1$calculate_gvar()
#> boundary (singular) fit: see help('isSingular')
#> $gvar
#> [1] 1.392268e-11
#> 

# Calculate phenotypic variance (pvar)
gvc1$calculate_pvar()
#> boundary (singular) fit: see help('isSingular')
#> $pvar
#> [1] 319911.6
#> 

# Calculate heritability (h2)
gvc1$calculate_herit()
#> boundary (singular) fit: see help('isSingular')
#> $h2
#> [1] 4.35204e-17
#>