Level 0 function that calculates the performance criterion as the sum of the queen (maternal) effect from the queen and the workers (direct) effect from her workers, as defined by Du et al. (2021). This can be seen as the expected value of the colony.
calcPerformanceCriterion(
x,
queenTrait = 1,
workersTrait = 2,
workersTraitFUN = sum,
use = "gv"
)numeric (column position) or character (column name), trait
that represents queen's effect on the colony value; if NULL
then this effect is 0
numeric (column position) or character (column name), trait
that represents workers' effect on the colony value; if NULL
then this effect is 0
function, that will be applied to the workers effect values of workers, default is sum (see examples), but note that the correct function will depend on how you will setup simulation!
character, the measure to use for the calculation, being either "gv" (genetic value),"ebv" (estimated breeding value), or "pheno" (phenotypic value)
integer when x is
Colony-class and a named list when x is
MultiColony-class, where names are colony IDs
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
calcSelectionCriterion and
calcInheritanceCriterion and as well as
vignette(topic = "QuantitativeGenetics", package = "SIMplyBee")
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)
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
drones <- createDrones(x = basePop[1], nInd = 1000)
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
droneGroups <- pullDroneGroupsFromDCA(drones, n = 10, nDrones = nFathersPoisson)
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
# Create a Colony and a MultiColony class
colony <- createColony(x = basePop[2])
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
colony <- cross(colony, drones = droneGroups[[1]])
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
colony <- buildUp(colony)
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
apiary <- createMultiColony(basePop[3:4], n = 2)
#> Error in createMultiColony(basePop[3:4], n = 2): object 'basePop' not found
apiary <- cross(apiary, drones = droneGroups[c(2, 3)])
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
apiary <- buildUp(apiary)
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
calcPerformanceCriterion(colony, queenTrait = 1, workersTrait = 2, workersTraitFUN = sum)
#> Error in is(x, class2 = "Colony"): object 'colony' not found
calcPerformanceCriterion(apiary, queenTrait = 1, workersTrait = 2, workersTraitFUN = sum)
#> Error in is(x, class2 = "Colony"): object 'apiary' not found
apiary[[2]] <- removeQueen(apiary[[2]])
#> Error in get(x = "SP", envir = .GlobalEnv): object 'SP' not found
calcPerformanceCriterion(apiary, queenTrait = 1,
workersTrait = 2, workersTraitFUN = sum)
#> Error in is(x, class2 = "Colony"): object 'apiary' not found