R: Simulate genetic values based on an unstructured model for...

unstr_asr_input {FieldSimR}

R Documentation

Simulate genetic values based on an unstructured model for GxE interaction - 'AlphaSimR' input parameters

Description

Creates a list of input parameters for 'AlphaSimR' to simulate genetic values in multiple environments for one or more traits based on an unstructured model for genotype-by-environment (GxE) interaction.
This function utilises the ability of 'AlphaSimR' to simulate correlated traits. The wrapper function unstr_asr_input() is used to specify the input parameters required in 'AlphaSimR', and can handle separable and non-separable structures between traits and environments (see below). After simulating the genetic values, the wrapper function unstr_asr_output can be used to generate a data frame with output values.

Usage

unstr_asr_input(
  ntraits = 1,
  nenvs = 2,
  mean = 0,
  var = 1,
  Tvar = NULL,
  Evar = NULL,
  corA = NULL,
  TcorA = NULL,
  EcorA = NULL,
  meanDD = NULL,
  varDD = NULL,
  TvarDD = NULL,
  EvarDD = NULL,
  corDD = NULL,
  TcorDD = NULL,
  EcorDD = NULL,
  relAA = NULL,
  TrelAA = NULL,
  ErelAA = NULL,
  corAA = NULL,
  TcorAA = NULL,
  EcorAA = NULL
)

Arguments

`ntraits`	Number of traits to be simulated.
`nenvs`	Number of environments to be simulated (minimum of two).
`mean`	A vector of mean genetic values for each environment-within-trait combination. If only one value is specified, all combinations will be assigned the same mean.
`var`	A vector of genetic variances for each environment-within-trait combination. If only one value is specified, all combinations will be assigned the same variance. Alternatively, if a separable structure between traits and environments is desired, `Tvar` and `Evar` can be specified.
`Tvar`	A vector of genetic variances for each trait. Must be provided in combination with `Evar`. Alternatively, `var` can be specified.
`Evar`	A vector of genetic variances for each environment. Must be provided in combination with `Tvar`. Alternatively, `var` can be specified.
`corA`	A matrix of additive genetic correlations between environment-within-trait combinations. By default, a diagonal matrix is constructed. Alternatively, `TcorA` and `EcorA` can be specified.
`TcorA`	A matrix of additive genetic correlations between traits. Must be provided in combination with `EcorA`. Alternatively, `corA` can be specified.
`EcorA`	A matrix of additive genetic correlations between environments. Must be provided in combination with `TcorA`. Alternatively, `corA` can be specified.
`meanDD`	A vector of mean dominance degrees for each environment-within-trait combination (similar to `mean`). If only one value is specified, all combinations will be assigned the same mean. By default, `meanDD = NULL` and dominance is not simulated.
`varDD`	A vector of dominance degree variances for each environment-within-trait combination (similar to `var`). If only one value is specified, all combinations will be assigned the same variance. Alternatively, if a separable structure between traits and environments is desired, `TvarDD` and `EvarDD` can be specified.
`TvarDD`	A vector of dominance degree variances for each trait (similar to `Tvar`). Must be provided in combination with `EvarDD`. Alternatively, `varDD` can be specified.
`EvarDD`	A vector of dominance degree variances for each environment (similar to `Evar`). Must be provided in combination with `TvarDD`. Alternatively, `varDD` can be specified.
`corDD`	A matrix of dominance degree correlations between environment-within-trait combinations (similar to `corA`). If not specified and dominance is simulated, a diagonal matrix is constructed. Alternatively, `TcorDD` and `EcorDD` can be specified.
`TcorDD`	A matrix of dominance degree correlations between traits (similar to `TcorA`). Must be provided in combination with `EcorDD`. Alternatively, `corDD` can be specified.
`EcorDD`	A matrix of dominance degree correlations between environments (similar to `EcorA`). Must be provided in combination with `TcorDD`. Alternatively, `corDD` can be specified.
`relAA`	A vector defining the relative magnitude of additive-by-additive (epistatic) variance to additive genetic variance for each environment-within-trait combination, that is in a diploid organism with allele frequency of 0.5. If only one value is specified, all environment-within-trait combinations will be assigned the same value. By default, `relAA = NULL` and epistasis is not simulated. Alternatively, if a separable structure between traits and environments is desired, `TrelAA` and `ErelAA` can be specified.
`TrelAA`	A vector defining the relative magnitude of epistatic variance to additive genetic variance for each trait. Must be provided in combination with `ErelAA`. Alternatively, `relAA` can be specified.
`ErelAA`	A vector defining the relative magnitude of epistatic variance to additive genetic variance for each environment. Must be provided in combination with `TrelAA`. Alternatively, `relAA` can be specified.
`corAA`	A matrix of epistatic correlations between environment-within-trait combinations (similar to `corA`). If not specified and epistasis is simulated, a diagonal matrix is constructed. Alternatively, `TcorAA` and `EcorAA` can be specified.
`TcorAA`	A matrix of epistatic correlations between traits (similar to `TcorA`). Must be provided in combination with `EcorAA`. Alternatively, `corAA` can be specified.
`EcorAA`	A matrix of epistatic correlations between environments (similar to `EcorA`). Must be provided in combination with `TcorAA`. Alternatively, `corAA` can be specified.

Details

unstr_asr_input can handle separable and non-separable structures between traits and environments.

For separable structures, provide (1) Tvar & Evar, and (2) TcorA & EcorA.
For non-separable structures, provide (1) var, and (2) corA.

Note: 'AlphaSimR' can simulate different biological effects (see: SimParam).

For additive traits use addTraitA().
For additive + dominance traits use addTraitAD().
For additive + epistatic traits use addTraitAE().
For additive + dominance + epistatic traits use addTraitADE().

Check the useVarA argument of these functions when simulating non-additive traits.

Value

A list with input parameters for 'AlphaSimR', which are used to simulate correlated genetic values based on an unstructured model for GxE interaction.

Examples

# Simulate genetic values with 'AlphaSimR' for two additive + dominance traits
# in two environments based on an unstructured model.

# 1. Define the genetic architecture of the simulated traits.
# Mean genetic values and mean dominance degrees.
mean <- c(4.9, 5.4, 235.2, 228.5) # Trait 1 x 2 environments, Trait 2 x 2 environments
meanDD <- c(0.4, 0.4, 0.1, 0.1) # Trait 1 and 2, same value for both environments

# Additive genetic variances and dominance degree variances.
var <- c(0.086, 0.12, 15.1, 8.5) # Trait 1 x 2 environments, Trait 2 x 2 environments
varDD <- 0.2 # Same value for all environment-within-trait combinations

# Additive genetic correlations between the two simulated traits.
TcorA <- matrix(c(
  1.0, 0.6,
  0.6, 1.0
), ncol = 2)

# Additive genetic correlations between the two simulated environments.
EcorA <- matrix(c(
  1.0, 0.2,
  0.2, 1.0
), ncol = 2)

# Dominance degree correlations between the four environment-within-trait combinations.
corDD <- diag(4) # Assuming independence

input_asr <- unstr_asr_input(
  ntraits = 2,
  nenvs = 2,
  mean = mean,
  var = var,
  TcorA = TcorA,
  EcorA = EcorA,
  meanDD = meanDD,
  varDD = varDD,
  corDD = corDD
)

[Package FieldSimR version 1.3.0 Index]