population: R6 class representing a population

In KosukeHamazaki/myBreedSimulatR: R Breeding Simulator for K.Hamazaki

R6 class representing a population

Description

population object store specific information about multiple individuals

Public fields

name

[string] Name of the population

generation

[integer] Generation of the population

specie

[specie class] Specie of the SNPs (see:specie)

traitInfo

[traitInfo class] Specific information of traits (see:traitInfo)

crossInfo

[crossInfo class] Information of crossing (including selection scheme) (see:crossInfo)

inds

[list] list of population's individuals

trialInfo

[trialInfo class] Specific information of field trial

phenotypicValues

[array] individual x traits x replication (3-dimensional array) of phenotypic values

verbose

[boolean] display information

Active bindings

nInd

[numeric] number of individual in the population

genoMat

[matrix] matrix of all the genotypes of the population encoded in allele doses. (individuals in row and markers in column)

trueAGVMat

[matrix] matrix of true additive genotypic values

trueDGVMat

[matrix] matrix of true dominant genotypic values

trueEGVMat

[matrix] matrix of true epistatic genotypic values

trueGVMat

[matrix] matrix of true genotypic values

trueAGVETMat

[matrix] matrix of true additive genotypic values specific to each trait

trueDGVETMat

[matrix] matrix of true dominant genotypic values specific to each trait

trueEGVETMat

[matrix] matrix of true epistatic genotypic values specific to each trait

trueGVETMat

[matrix] matrix of true genotypic values specific to each trait

trueAGVCTMat

[matrix] matrix of true additive genotypic values common across trait

trueDGVCTMat

[matrix] matrix of true dominant genotypic values common across trait

trueEGVCTMat

[matrix] matrix of true epistatic genotypic values common across trait

trueGVCTMat

[matrix] matrix of true genotypic values common across trait

haploArray

[array] 3-dimensional array of all the haplotypes of the population encoded with 0, 1. (individuals in row, markers in column, and ploidy in 3rd dimension)

af

[named vector] allele frequency

maf

[named vector] minor allele frequency

heteroRate

[named vector] ratio of heterozygotes

Methods

Public methods

• population$new()

• population$addInds()

• population$remInds()

• population$inputTrialInfo()

• population$inputPhenotypicValues()

• population$print()

• population$plot()

• population$clone()

---

Method new()

Create a new population object.

Usage

population$new(
  name = NULL,
  generation = NA,
  traitInfo = NULL,
  crossInfo = NULL,
  inds = list(),
  verbose = TRUE
)

Arguments

name

[string] name of the population

generation

[integer] Generation of the population

traitInfo

[traitInfo class] Specific information of traits (see:traitInfo)

crossInfo

[crossInfo class] Information of crossing (including selection scheme) (see:crossInfo)

inds

[individual class or list] list of individuals of the population (see:individual)

verbose

[boolean] display information

Returns

A new 'population' object.

Examples

### create simulation information
mySimInfo <- simInfo$new(simName = "Simulation Example",
                         simGeno = TRUE,
                         simPheno = TRUE,
                         nSimGeno = 1,
                         nSimPheno = 3,
                         nCoreMax = 4,
                         nCorePerGeno = 1,
                         nCorePerPheno = 3,
                         saveDataFileName = NULL)
### create specie information
mySpec <- specie$new(nChr = 3,
                     lChr = c(100, 150, 200),
                     specName = "Example 1",
                     ploidy = 2,
                     mutRate = 10^-8,
                     recombRate = 10^-6,
                     chrNames = c("C1", "C2", "C3"),
                     nLoci = c(3, 4, 5),
                     effPopSize = 3,
                     simInfo = mySimInfo,
                     verbose = TRUE)
### create lociInfo object
myLoci <- lociInfo$new(genoMap = NULL, specie = mySpec)
### create traitInfo object
myTrait <- traitInfo$new(lociInfo = myLoci,
                         nMarkers = c(2, 4, 3),
                         nTraits = 2,
                         nQTLs = matrix(c(1, 0, 2,
                                          1, 0, 1),
                                        nrow = 2,
                                        byrow = TRUE),
                         actionTypeEpiSimple = TRUE,
                         qtlOverlap = TRUE,
                         nOverlap = c(1, 0, 1),
                         effCor = 0.6,
                         propDomi = 0.2,
                         interactionMean = c(1, 0))
plot(myTrait, alphaMarker = 0.4)
### simulate haplotype
rawHaplo1 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo1) <- paste0("Locus_", 1:(3 + 4 + 5))
myHaplo1 <- myBreedSimulatR::haplotype$new(lociInfo = myLoci,
                                           haplo = rawHaplo1)
rawHaplo2 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo2) <- paste0("Locus_", 1:(3 + 4 + 5))
myHaplo2 <- myBreedSimulatR::haplotype$new(lociInfo = myLoci,
                                           haplo = rawHaplo2)
### create individuals:
myInd1 <-  individual$new(name = "Ind 1",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan1",
                          parent2 = "OtouSan1",
                          haplo = myHaplo1,
                          verbose = TRUE)
myInd2 <-  individual$new(name = "Ind 2",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan2",
                          parent2 = "OtouSan2",
                          haplo = myHaplo2,
                          verbose = TRUE)
myInd3 <-  individual$new(name = "Ind 3",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan1",
                          parent2 = "OtouSan1",
                          haplo = myHaplo1,
                          verbose = TRUE)
myPop <- population$new(name = "My Population 1",
                        generation = 1,
                        traitInfo = myTrait,
                        inds = list(myInd1, myInd2, myInd3),
                        verbose = FALSE)
myPop$trueEGVMat
myPop$plot(plotTarget = "trueAGV",
           plotType = "violin")
myPop$plot(plotTarget = "trueGV",
           plotType = "scatter",
           scatterAxes = c(2, 1))

---

Method addInds()

Add individuals to the population

Usage

population$addInds(inds)

Arguments

inds

[individual class or list] list of individuals of the population (see:individual)

Examples

# create new individual

rawHaplo4 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo4) <- sprintf(fmt = paste0("SNP%0", 2,"i"),
                              1:(3 + 4 + 5))
haplo4 <- haplotype$new(lociInfo = myLoci,
                       haplo = rawHaplo4)
myInd4 <-  individual$new(name = "Ind 4",
                         specie = mySpec,
                         parent1 = "OkaaSan",
                         parent2 = "OtouSan",
                         haplo = haplo4,
                         verbose = FALSE)

# add individual
print(self)
self$addInds(myInd4)
print(self)

---

Method remInds()

Remove individuals from the population

Usage

population$remInds(indNames)

Arguments

indNames

[character] character vetcor of the individuals' names

Examples

print(self)
self$remInds("Ind 2")
print(self)

---

Method inputTrialInfo()

Remove individuals from the population

Usage

population$inputTrialInfo(
  trialInfoNow = NULL,
  herit = NULL,
  nRep = NULL,
  multiTraitsAsEnvs = FALSE,
  envSpecificEffects = NULL,
  residCor = NULL,
  seedResid = NA
)

Arguments

trialInfoNow

[trialInfo class] trialInfo class object

herit

[numeric] Heritability for each trait (plot-based/line-based)

nRep

[numeric] Replication of the field trial (common to all traits)

multiTraitsAsEnvs

[logical] Treat multiple traits as multiple environments or not

envSpecificEffects

[numeric] Effects specific to each environments / treatments. If 'multiTraitsAsEnvs = FALSE', envSpecificEffects will be 0 for all traits.

residCor

[matrix] Residual correlation between traits

seedResid

[numeric] Random seed for selecting residuals

Examples

print(self$trialInfo)
self$inputTrialInfo()
print(self$trialInfo)

---

Method inputPhenotypicValues()

Input phenotypic values

Usage

population$inputPhenotypicValues(phenotypicValues = NULL)

Arguments

phenotypicValues

[array] individual x traits x replication (3-dimensional array) of phenotypic values If you use real phenotypic data, please specify your phenotypic values. If you simulate phenotypic data, please set 'phenotypicValues = NULL'.

---

Method print()

Display informations about the object

Usage

population$print()

---

Method plot()

Draw figures for visualization of each data (GVs, phenotypes, and GRM)

Usage

population$plot(
  plotTarget = "trueGV",
  plotType = "box",
  scatterAxes = 1:min(2, self$traitInfo$nTraits)
)

Arguments

plotTarget

[character] Target of figure, select either one of "trueAGV", "trueDGV", "trueEGV", "trueGV", "trueAGVET", "trueDGVET", "trueEGVET", "trueGVET", "trueAGVCT", "trueDGVCT", "trueEGVCT", "trueGVCT", "phenotypicValues".

plotType

[character] We offer "box", "violin", "scatter" (or "scatter3d") to draw figures for genotypic/phenotypic values.

scatterAxes

[numeric/character] If you select "scatter" option for 'plotType', you should design which traits will be assigned to each axis. You can define by indices of traits or trait names.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

population$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## ------------------------------------------------
## Method `population$new`
## ------------------------------------------------

### create simulation information
mySimInfo <- simInfo$new(simName = "Simulation Example",
                         simGeno = TRUE,
                         simPheno = TRUE,
                         nSimGeno = 1,
                         nSimPheno = 3,
                         nCoreMax = 4,
                         nCorePerGeno = 1,
                         nCorePerPheno = 3,
                         saveDataFileName = NULL)
### create specie information
mySpec <- specie$new(nChr = 3,
                     lChr = c(100, 150, 200),
                     specName = "Example 1",
                     ploidy = 2,
                     mutRate = 10^-8,
                     recombRate = 10^-6,
                     chrNames = c("C1", "C2", "C3"),
                     nLoci = c(3, 4, 5),
                     effPopSize = 3,
                     simInfo = mySimInfo,
                     verbose = TRUE)
### create lociInfo object
myLoci <- lociInfo$new(genoMap = NULL, specie = mySpec)
### create traitInfo object
myTrait <- traitInfo$new(lociInfo = myLoci,
                         nMarkers = c(2, 4, 3),
                         nTraits = 2,
                         nQTLs = matrix(c(1, 0, 2,
                                          1, 0, 1),
                                        nrow = 2,
                                        byrow = TRUE),
                         actionTypeEpiSimple = TRUE,
                         qtlOverlap = TRUE,
                         nOverlap = c(1, 0, 1),
                         effCor = 0.6,
                         propDomi = 0.2,
                         interactionMean = c(1, 0))
plot(myTrait, alphaMarker = 0.4)
### simulate haplotype
rawHaplo1 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo1) <- paste0("Locus_", 1:(3 + 4 + 5))
myHaplo1 <- myBreedSimulatR::haplotype$new(lociInfo = myLoci,
                                           haplo = rawHaplo1)
rawHaplo2 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo2) <- paste0("Locus_", 1:(3 + 4 + 5))
myHaplo2 <- myBreedSimulatR::haplotype$new(lociInfo = myLoci,
                                           haplo = rawHaplo2)
### create individuals:
myInd1 <-  individual$new(name = "Ind 1",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan1",
                          parent2 = "OtouSan1",
                          haplo = myHaplo1,
                          verbose = TRUE)
myInd2 <-  individual$new(name = "Ind 2",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan2",
                          parent2 = "OtouSan2",
                          haplo = myHaplo2,
                          verbose = TRUE)
myInd3 <-  individual$new(name = "Ind 3",
                          specie = myTrait$lociInfo$specie,
                          traitInfo = myTrait,
                          parent1 = "OkaaSan1",
                          parent2 = "OtouSan1",
                          haplo = myHaplo1,
                          verbose = TRUE)
myPop <- population$new(name = "My Population 1",
                        generation = 1,
                        traitInfo = myTrait,
                        inds = list(myInd1, myInd2, myInd3),
                        verbose = FALSE)
myPop$trueEGVMat
myPop$plot(plotTarget = "trueAGV",
           plotType = "violin")
myPop$plot(plotTarget = "trueGV",
           plotType = "scatter",
           scatterAxes = c(2, 1))

## ------------------------------------------------
## Method `population$addInds`
## ------------------------------------------------

# create new individual

rawHaplo4 <- matrix(sample(c(0, 1), (3 + 4 + 5) * 2, replace = TRUE),
                    nrow = 2)
colnames(rawHaplo4) <- sprintf(fmt = paste0("SNP%0", 2,"i"),
                              1:(3 + 4 + 5))
haplo4 <- haplotype$new(lociInfo = myLoci,
                       haplo = rawHaplo4)
myInd4 <-  individual$new(name = "Ind 4",
                         specie = mySpec,
                         parent1 = "OkaaSan",
                         parent2 = "OtouSan",
                         haplo = haplo4,
                         verbose = FALSE)

# add individual
print(self)
self$addInds(myInd4)
print(self)

## ------------------------------------------------
## Method `population$remInds`
## ------------------------------------------------

print(self)
self$remInds("Ind 2")
print(self)

## ------------------------------------------------
## Method `population$inputTrialInfo`
## ------------------------------------------------

print(self$trialInfo)
self$inputTrialInfo()
print(self$trialInfo)

KosukeHamazaki/myBreedSimulatR documentation built on Aug. 31, 2024, 3:55 p.m.