calcInheritanceCriterion {SIMplyBee}

Calculate the inheritance criterion

Description

Level 0 function that calculates the inheritance criterion as the sum of the queen (maternal) and workers (direct) effect from the queen, as defined by Du et al. (2021). This can be seen as the expected value of drones from the queen or half the expected value of virgin queens from the queen.

Usage

calcInheritanceCriterion(x, queenTrait = 1, workersTrait = 2, use = "gv")

Arguments

x

Pop-class, Colony-class or MultiColony-class

queenTrait

numeric (column position) or character (column name), trait that represents queen's effect on the colony value; if NULL then this effect is 0

workersTrait

numeric (column position) or character (column name), trait that represents workers' effect on the colony value; if NULL then this effect is 0

use

character, the measure to use for the calculation, being either "gv" (genetic value), "ebv" (estimated breeding value), or "pheno" (phenotypic value)

Value

integer when x is Colony-class and a named list when x is MultiColony-class, where names are colony IDs

References

Du, M., et al. (2021) Short-term effects of controlled mating and selection on the genetic variance of honeybee populations. Heredity 126, 733–747. doi:/10.1038/s41437-021-00411-2

See Also

calcSelectionCriterion and calcPerformanceCriterion and as well as vignette(topic = "QuantitativeGenetics", package = "SIMplyBee")

Examples

founderGenomes <- quickHaplo(nInd = 8, nChr = 1, segSites = 100)
SP <- SimParamBee$new(founderGenomes)
meanA <- c(10, 10 / SP$nWorkers)
varA <- c(1, 1 / SP$nWorkers)
corA <- matrix(data = c( 1.0, -0.5,
                        -0.5,  1.0), nrow = 2, byrow = TRUE)
SP$addTraitA(nQtlPerChr = 100, mean = meanA, var = varA, corA = corA,
name = c("queenTrait", "workersTrait"))
varE <- c(3, 3 / SP$nWorkers)
corE <- matrix(data = c(1.0, 0.3,
                        0.3, 1.0), nrow = 2, byrow = TRUE)
SP$setVarE(varE = varE, corE = corE)
basePop <- createVirginQueens(founderGenomes)

drones <- createDrones(x = basePop[1], nInd = 1000)
droneGroups <- pullDroneGroupsFromDCA(drones, n = 10, nDrones = nFathersPoisson)

# Create a Colony and a MultiColony class
colony <- createColony(x = basePop[2])
colony <- cross(colony, drones = droneGroups[[1]])

apiary <- createMultiColony(basePop[3:4], n = 2)
apiary <- cross(apiary, drones = droneGroups[c(2, 3)])

calcInheritanceCriterion(colony, queenTrait = 1, workersTrait = 2)
calcInheritanceCriterion(apiary, queenTrait = 1, workersTrait = 2)

apiary[[2]] <- removeQueen(apiary[[2]])
calcInheritanceCriterion(apiary, queenTrait = 1, workersTrait = 2)