reportGV: Generates a genetic value report for a provided pedigree.
In rmsharp/nprcmanager: Genetic Tools for Colony Management

Description Usage Arguments Value Examples

This is the main function for the Genetic Value Analysis.

reportGV(
  ped,
  guIter = 5000,
  guThresh = 1,
  pop = NULL,
  byID = TRUE,
  updateProgress = NULL
)

`ped`	The pedigree information in data.frame format
`guIter`	Integer indicating the number of iterations for the gene-drop analysis. Default is 5000 iterations
`guThresh`	Integer indicating the threshold number of animals for defining a unique allele. Default considers an allele "unique" if it is found in only 1 animal.
`pop`	Character vector with animal IDs to consider as the population of interest. The default is NULL.
`byID`	Logical variable of length 1 that is passed through to eventually be used by `alleleFreq()`, which calculates the count of each allele in the provided vector. If `byID` is TRUE and ids are provided, the function will only count the unique alleles for an individual (homozygous alleles will be counted as 1).
`updateProgress`	Function or NULL. If this function is defined, it will be called during each iteration to update a `shiny::Progress` object.

A dataframe with the genetic value report. Animals are ranked in order of descending value.

library(nprcgenekeepr)
examplePedigree <- nprcgenekeepr::examplePedigree
breederPed <- qcStudbook(examplePedigree, minParentAge = 2,
                         reportChanges = FALSE,
                         reportErrors = FALSE)
focalAnimals <- breederPed$id[!(is.na(breederPed$sire) &
                                  is.na(breederPed$dam)) &
                                is.na(breederPed$exit)]
ped <- setPopulation(ped = breederPed, ids = focalAnimals)
trimmedPed <- trimPedigree(focalAnimals, breederPed)
probands <- ped$id[ped$population]
ped <- trimPedigree(probands, ped, removeUninformative = FALSE,
                    addBackParents = FALSE)
geneticValue <- reportGV(ped, guIter = 50, # should be >= 1000
                         guThresh = 3,
                         byID = TRUE,
                         updateProgress = NULL)
trimmedGeneticValue <- reportGV(trimmedPed, guIter = 50, # should be >= 1000
                                guThresh = 3,
                                byID = TRUE,
                                updateProgress = NULL)
rpt <- trimmedGeneticValue[["report"]]
kmat <- trimmedGeneticValue[["kinship"]]
f <- trimmedGeneticValue[["total"]]
mf <- trimmedGeneticValue[["maleFounders"]]
ff <- trimmedGeneticValue[["femaleFounders"]]
nmf <- trimmedGeneticValue[["nMaleFounders"]]
nff <- trimmedGeneticValue[["nFemaleFounders"]]
fe <- trimmedGeneticValue[["fe"]]
fg <- trimmedGeneticValue[["fg"]]