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Simulation parameters

Source: R/Class-SimParam.R
SimParam.Rd

Container for global simulation parameters. Saving this object as SP will allow it to be accessed by function defaults.

Note

By default the founder population is the population used to initalize the SimParam object. This population can be changed by replacing the population in the founderPop slot. You must run resetPop on any existing populations to obtain the new trait values.

Public fields

nThreads

number of threads used on platforms with OpenMP support

snpChips

list of SNP chips

invalidQtl

list of segregating sites that aren't valid QTL

invalidSnp

list of segregating sites that aren't valid SNP

founderPop

founder population used for variance scaling

finalizePop

function applied to newly created populations. Currently does nothing and should only be changed by expert users.

allowEmptyPop

if true, population arguments with nInd=0 will return an empty population with a warning instead of an error.

v

the crossover interference parameter for a gamma model of recombination. A value of 1 indicates no crossover interference (e.g. Haldane mapping function). A value of 2.6 approximates the degree of crossover interference implied by the Kosambi mapping function. (default is 2.6)

p

the proportion of crossovers coming from a non-interfering pathway. (default is 0)

quadProb

the probability of quadrivalent pairing in an autopolyploid. (default is 0)

Active bindings

traitNames

vector of trait names

snpChipNames

vector of chip names

traits

list of traits

nChr

number of chromosomes

nTraits

number of traits

nSnpChips

number of SNP chips

segSites

segregating sites per chromosome

sexes

sexes used for mating

sepMap

are there seperate genetic maps for males and females

genMap

list of chromosome genetic maps

femaleMap

list of chromosome genetic maps for females

maleMap

list of chromosome genetic maps for males

centromere

position of centromeres genetic map

femaleCentromere

position of centromeres on female genetic map

maleCentromere

position of centromeres on male genetic map

lastId

last ID number assigned

isTrackPed

is pedigree being tracked

pedigree

pedigree matrix for all individuals

isTrackRec

is recombination being tracked

recHist

list of historic recombination events

haplotypes

list of computed IBD haplotypes

varA

additive genetic variance in founderPop

varG

total genetic variance in founderPop

varE

default error variance

version

the version of AlphaSimR used to generate this object

activeQtl

a LociMap representing all active QTL in simulation

qtlIndex

a list of vectors giving trait specific QTL indices relative to all active QTL

Methods

Public methods

Method new()

Starts the process of building a new simulation by creating a new SimParam object and assigning a founder population to the class. It is recommended that you save the object with the name "SP", because subsequent functions will check your global environment for an object of this name if their simParam arguments are NULL. This allows you to call these functions without explicitly supplying a simParam argument with every call.

Usage

SimParam$new(founderPop)

Arguments

founderPop

an object of MapPop-class

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)

Method setTrackPed()

Sets pedigree tracking for the simulation. By default pedigree tracking is turned off. When turned on, the pedigree of all individuals created will be tracked, except those created by hybridCross. Turning off pedigree tracking will turn off recombination tracking if it is turned on.

Usage

SimParam$setTrackPed(isTrackPed, force = FALSE)

Arguments

isTrackPed

should pedigree tracking be on.

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$setTrackPed(TRUE)

Method setTrackRec()

Sets recombination tracking for the simulation. By default recombination tracking is turned off. When turned on recombination tracking will also turn on pedigree tracking. Recombination tracking keeps records of all individuals created, except those created by hybridCross, because their pedigree is not tracked.

Usage

SimParam$setTrackRec(isTrackRec, force = FALSE)

Arguments

isTrackRec

should recombination tracking be on.

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$setTrackRec(TRUE)

Method resetPed()

Resets the internal lastId, the pedigree and recombination tracking (if in use) to the supplied lastId. Be careful using this function because it may introduce a bug if you use individuals from the deleted portion of the pedigree.

Usage

SimParam$resetPed(lastId = 0L)

Arguments

lastId

last ID to include in pedigree

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}

#Create population
pop = newPop(founderPop, simParam=SP)
pop@id # 1:10

#Create another population after reseting pedigree
SP$resetPed()
pop2 = newPop(founderPop, simParam=SP)
pop2@id # 1:10

Method restrSegSites()

Sets restrictions on which segregating sites can serve as a SNP and/or QTL. The default behavior of AlphaSimR is to randomly sample QTL or SNP from all eligible sites and then mark the sampled sites ineligible to be sampled as the other type (e.g. if a site is sampled as a QTL it will be marked as ineligible to be sampled as a SNP). This behavior is designed to produce the most challenging scenario for genomic selection when the markers used for prediction are not causal.

Setting overlap=TRUE will prevent the addition of loci to the ineligible list, but it won't remove sites already added to these lists. Thus, timing of when restrSegSites is called matters. It should be called before any addTrait or addSnpChip functions with the overlap=TRUE argument to freely allow loci to overlap.

The minQtlPerChr and minSnpPerChr arguments can be used with overlap=FALSE to preallocate sites as QTL and SNP respectively. This option is useful when simulating multiple traits and/or SNP chips, because it can be used to guarantee that enough eligible sites are available when running addTrait and or addSnpChip functions.

Usage

SimParam$restrSegSites(
  minQtlPerChr = NULL,
  minSnpPerChr = NULL,
  excludeQtl = NULL,
  excludeSnp = NULL,
  overlap = FALSE,
  minSnpFreq = NULL
)

Arguments

minQtlPerChr

the minimum number of segregating sites for QTLs. Can be a single value or a vector values for each chromosome.

minSnpPerChr

the minimum number of segregating sites for SNPs. Can be a single value or a vector values for each chromosome.

excludeQtl

an optional vector of segregating site names to exclude from consideration as a viable QTL.

excludeSnp

an optional vector of segregating site names to exclude from consideration as a viable SNP.

overlap

should SNP and QTL sites be allowed to overlap.

minSnpFreq

minimum allowable frequency for SNP loci. No minimum SNP frequency is used if value is NULL.

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$restrSegSites(minQtlPerChr=5, minSnpPerChr=5)

Method setSexes()

Changes how sexes are determined in the simulation. The default sexes is "no", indicating all individuals are hermaphrodites. To add sexes to the simulation, run this function with "yes_sys" or "yes_rand". The value "yes_sys" will systematically assign sexes to newly created individuals as first male and then female. Populations with an odd number of individuals will have one more male than female. The value "yes_rand" will randomly assign a sex to each individual.

Usage

SimParam$setSexes(sexes, force = FALSE)

Arguments

sexes

acceptable value are "no", "yes_sys", or "yes_rand"

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$setSexes("yes_sys")

Method setFounderHap()

Allows for the manual setting of founder haplotypes. This functionality is not fully documented, because it is still experimental.

Usage

SimParam$setFounderHap(hapMap)

Arguments

hapMap

a list of founder haplotypes

Method addSnpChip()

Randomly assigns eligible SNPs to a SNP chip

Usage

SimParam$addSnpChip(nSnpPerChr, minSnpFreq = NULL, refPop = NULL, name = NULL)

Arguments

nSnpPerChr

number of SNPs per chromosome. Can be a single value or nChr values.

minSnpFreq

minimum allowable frequency for SNP loci. If NULL, no minimum frequency is used.

refPop

reference population for calculating SNP frequency. If NULL, the founder population is used.

name

optional name for chip

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addSnpChip(10)

Method addSnpChipByName()

Assigns SNPs to a SNP chip by supplying marker names. This function does check against excluded SNPs and will not add the SNPs to the list of excluded QTL for the purpose of avoiding overlap between SNPs and QTL. Excluding these SNPs from being used as QTL can be accomplished using the excludeQtl argument in SimParam's restrSegSites function.

Usage

SimParam$addSnpChipByName(markers, name = NULL)

Arguments

markers

a vector of names for the markers

name

optional name for chip

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addSnpChipByName(c("1_1","1_3"))

Method addStructuredSnpChip()

Randomly selects the number of snps in structure and then assigns them to chips based on structure

Usage

SimParam$addStructuredSnpChip(nSnpPerChr, structure, force = FALSE)

Arguments

nSnpPerChr

number of SNPs per chromosome. Can be a single value or nChr values.

structure

a matrix. Rows are snp chips, columns are chips. If value is true then that snp is on that chip.

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

Method addTraitA()

Randomly assigns eligible QTLs for one or more additive traits. If simulating more than one trait, all traits will be pleiotropic with correlated additive effects.

Usage

SimParam$addTraitA(
  nQtlPerChr,
  mean = 0,
  var = 1,
  corA = NULL,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

corA

a matrix of correlations between additive effects

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitA(10)

Method addTraitAD()

Randomly assigns eligible QTLs for one or more traits with dominance. If simulating more than one trait, all traits will be pleiotropic with correlated effects.

Usage

SimParam$addTraitAD(
  nQtlPerChr,
  mean = 0,
  var = 1,
  meanDD = 0,
  varDD = 0,
  corA = NULL,
  corDD = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

meanDD

mean dominance degree

varDD

variance of dominance degree

corA

a matrix of correlations between additive effects

corDD

a matrix of correlations between dominance degrees

useVarA

tune according to additive genetic variance if true. If FALSE, tuning is performed according to total genetic variance.

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitAD(10, meanDD=0.5)

Method altAddTraitAD()

An alternative method for adding a trait with additive and dominance effects to an AlphaSimR simulation. The function attempts to create a trait matching user defined values for number of QTL, inbreeding depression, additive genetic variance and dominance genetic variance.

Usage

SimParam$altAddTraitAD(
  nQtlPerChr,
  mean = 0,
  varA = 1,
  varD = 0,
  inbrDepr = 0,
  limMeanDD = c(0, 1.5),
  limVarDD = c(0, 0.5),
  silent = FALSE,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

desired mean of the trait

varA

desired additive variance

varD

desired dominance variance

inbrDepr

desired inbreeding depression, see details

limMeanDD

limits for meanDD, see details

limVarDD

limits for varDD, see details

silent

should summary details be printed to the console

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait

Details

This function will always add a trait to 'SimParam', unless an error occurs with picking QTLs. The resulting trait will always have the desired mean and additive genetic variance. However, it may not have the desired values for inbreeding depression and dominance variance. Thus, it is strongly recommended to check the output printed to the console to determine how close the trait's parameters came to these desired values.

The mean and additive genetic variance will always be achieved exactly. The function attempts to achieve the desired dominance variance and inbreeding depression while staying within the user supplied constraints for the acceptable range of dominance degree mean and variance. If the desired values are not being achieved, the acceptable range need to be increased and/or the number of QTL may need to be increased. There are not limits to setting the range for dominance degree mean and variance, but care should be taken to with regards to the biological feasibility of the limits that are supplied. The default limits were somewhat arbitrarily set, so I make not claim to how reasonable these limits are for routine use.

Inbreeding depression in this function is defined as the difference in mean genetic value between a population with the same allele frequency as the reference population (population used to initialize SimParam) in Hardy-Weinberg equilibrium compared to a population with the same allele frequency that is fully inbred. This is equivalent to the amount the mean of a population increases when going from an inbreeding coefficient of 1 (fully inbred) to a population with an inbreeding coefficient of 0 (Hardy-Weinberg equilibrium). Note that the sign of the value should (usually) be positive. This corresponds to a detrimental effect of inbreeding when higher values of the trait are considered biologically beneficial.

Summary information on this trait is printed to the console when silent=FALSE. The summary information reports the inbreeding depression and dominance variance for the population as well as the dominance degree mean and variance applied to the trait.

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$altAddTraitAD(nQtlPerChr=10, mean=0, varA=1, varD=0.05, inbrDepr=0.2)

Method addTraitAG()

Randomly assigns eligible QTLs for one or more additive GxE traits. If simulating more than one trait, all traits will be pleiotropic with correlated effects.

Usage

SimParam$addTraitAG(
  nQtlPerChr,
  mean = 0,
  var = 1,
  varGxE = 1e-06,
  varEnv = 0,
  corA = NULL,
  corGxE = NULL,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

varGxE

a vector of total genotype-by-environment variances for the traits

varEnv

a vector of environmental variances for one or more traits

corA

a matrix of correlations between additive effects

corGxE

a matrix of correlations between GxE effects

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitAG(10, varGxE=2)

Method addTraitADG()

Randomly assigns eligible QTLs for a trait with dominance and GxE.

Usage

SimParam$addTraitADG(
  nQtlPerChr,
  mean = 0,
  var = 1,
  varEnv = 0,
  varGxE = 1e-06,
  meanDD = 0,
  varDD = 0,
  corA = NULL,
  corDD = NULL,
  corGxE = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

varEnv

a vector of environmental variances for one or more traits

varGxE

a vector of total genotype-by-environment variances for the traits

meanDD

mean dominance degree

varDD

variance of dominance degree

corA

a matrix of correlations between additive effects

corDD

a matrix of correlations between dominance degrees

corGxE

a matrix of correlations between GxE effects

useVarA

tune according to additive genetic variance if true

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitADG(10, meanDD=0.5, varGxE=2)

Method addTraitAE()

Randomly assigns eligible QTLs for one or more additive and epistasis traits. If simulating more than one trait, all traits will be pleiotropic with correlated additive effects.

Usage

SimParam$addTraitAE(
  nQtlPerChr,
  mean = 0,
  var = 1,
  relAA = 0,
  corA = NULL,
  corAA = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

relAA

the relative value of additive-by-additive variance compared to additive variance in a diploid organism with allele frequency 0.5

corA

a matrix of correlations between additive effects

corAA

a matrix of correlations between additive-by-additive effects

useVarA

tune according to additive genetic variance if true. If FALSE, tuning is performed according to total genetic variance.

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitAE(10, relAA=0.1)

Method addTraitADE()

Randomly assigns eligible QTLs for one or more traits with dominance and epistasis. If simulating more than one trait, all traits will be pleiotropic with correlated effects.

Usage

SimParam$addTraitADE(
  nQtlPerChr,
  mean = 0,
  var = 1,
  meanDD = 0,
  varDD = 0,
  relAA = 0,
  corA = NULL,
  corDD = NULL,
  corAA = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

meanDD

mean dominance degree

varDD

variance of dominance degree

relAA

the relative value of additive-by-additive variance compared to additive variance in a diploid organism with allele frequency 0.5

corA

a matrix of correlations between additive effects

corDD

a matrix of correlations between dominance degrees

corAA

a matrix of correlations between additive-by-additive effects

useVarA

tune according to additive genetic variance if true. If FALSE, tuning is performed according to total genetic variance.

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitADE(10)

Method addTraitAEG()

Randomly assigns eligible QTLs for one or more additive and epistasis GxE traits. If simulating more than one trait, all traits will be pleiotropic with correlated effects.

Usage

SimParam$addTraitAEG(
  nQtlPerChr,
  mean = 0,
  var = 1,
  relAA = 0,
  varGxE = 1e-06,
  varEnv = 0,
  corA = NULL,
  corAA = NULL,
  corGxE = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

relAA

the relative value of additive-by-additive variance compared to additive variance in a diploid organism with allele frequency 0.5

varGxE

a vector of total genotype-by-environment variances for the traits

varEnv

a vector of environmental variances for one or more traits

corA

a matrix of correlations between additive effects

corAA

a matrix of correlations between additive-by-additive effects

corGxE

a matrix of correlations between GxE effects

useVarA

tune according to additive genetic variance if true. If FALSE, tuning is performed according to total genetic variance.

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitAEG(10, varGxE=2)

Method addTraitADEG()

Randomly assigns eligible QTLs for a trait with dominance, epistasis and GxE.

Usage

SimParam$addTraitADEG(
  nQtlPerChr,
  mean = 0,
  var = 1,
  varEnv = 0,
  varGxE = 1e-06,
  meanDD = 0,
  varDD = 0,
  relAA = 0,
  corA = NULL,
  corDD = NULL,
  corAA = NULL,
  corGxE = NULL,
  useVarA = TRUE,
  gamma = FALSE,
  shape = 1,
  force = FALSE,
  name = NULL
)

Arguments

nQtlPerChr

number of QTLs per chromosome. Can be a single value or nChr values.

mean

a vector of desired mean genetic values for one or more traits

var

a vector of desired genetic variances for one or more traits

varEnv

a vector of environmental variances for one or more traits

varGxE

a vector of total genotype-by-environment variances for the traits

meanDD

mean dominance degree

varDD

variance of dominance degree

relAA

the relative value of additive-by-additive variance compared to additive variance in a diploid organism with allele frequency 0.5

corA

a matrix of correlations between additive effects

corDD

a matrix of correlations between dominance degrees

corAA

a matrix of correlations between additive-by-additive effects

corGxE

a matrix of correlations between GxE effects

useVarA

tune according to additive genetic variance if true

gamma

should a gamma distribution be used instead of normal

shape

the shape parameter for the gamma distribution (the rate/scale parameter of the gamma distribution is accounted for via the desired level of genetic variance, the var argument)

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing.

name

optional name for trait(s)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitADEG(10, meanDD=0.5, varGxE=2)

Method manAddTrait()

Manually add a new trait to the simulation. Trait must be formatted as a LociMap-class. If the trait is not already formatted, consider using importTrait.

Usage

SimParam$manAddTrait(lociMap, varE = NA_real_, force = FALSE)

Arguments

lociMap

a new object descended from LociMap-class

varE

default error variance for phenotype, optional

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing

Method importTrait()

Manually add a new trait(s) to the simulation. Unlike the manAddTrait function, this function does not require formatting the trait as a LociMap-class. The formatting is performed automatically for the user, with more user friendly data.frames or matrices taken as inputs. This function only works for A and AD trait types.

Usage

SimParam$importTrait(
  markerNames,
  addEff,
  domEff = NULL,
  intercept = NULL,
  name = NULL,
  varE = NULL,
  force = FALSE
)

Arguments

markerNames

a vector of names for the QTL

addEff

a matrix of additive effects (nLoci x nTraits). Alternatively, a vector of length nLoci can be supplied for a single trait.

domEff

optional dominance effects for each locus

intercept

optional intercepts for each trait

name

optional name(s) for the trait(s)

varE

default error variance for phenotype, optional

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing

Method switchTrait()

Switch a trait in the simulation.

Usage

SimParam$switchTrait(traitPos, lociMap, varE = NA_real_, force = FALSE)

Arguments

traitPos

an integer indicate which trait to switch

lociMap

a new object descended from LociMap-class

varE

default error variance for phenotype, optional

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing

Method removeTrait()

Remove a trait from the simulation

Usage

SimParam$removeTrait(traits, force = FALSE)

Arguments

traits

an integer vector indicating which traits to remove

force

should the check for a running simulation be ignored. Only set to TRUE if you know what you are doing

Method setVarE()

Defines a default values for error variances used in setPheno. These defaults will be used to automatically generate phenotypes when new populations are created. See the details section of setPheno for more information about each arguments and how they should be used.

Usage

SimParam$setVarE(h2 = NULL, H2 = NULL, varE = NULL, corE = NULL)

Arguments

h2

a vector of desired narrow-sense heritabilities

H2

a vector of desired broad-sense heritabilities

varE

a vector or matrix of error variances

corE

an optional matrix of error correlations

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitA(10)
SP$setVarE(h2=0.5)

Method setCorE()

Defines a correlation structure for default error variances. You must call setVarE first to define the default error variances.

Usage

SimParam$setCorE(corE)

Arguments

corE

a correlation matrix for the error variances

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$addTraitA(10, mean=c(0,0), var=c(1,1), corA=diag(2))
SP$setVarE(varE=c(1,1))
E = 0.5*diag(2)+0.5 #Positively correlated error
SP$setCorE(E)

Method rescaleTraits()

Linearly scales all traits to achieve desired values of means and variances in the founder population.

Usage

SimParam$rescaleTraits(
  mean = 0,
  var = 1,
  varEnv = 0,
  varGxE = 1e-06,
  useVarA = TRUE
)

Arguments

mean

a vector of new trait means

var

a vector of new trait variances

varEnv

a vector of new environmental variances

varGxE

a vector of new GxE variances

useVarA

tune according to additive genetic variance if true

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10)

#Create population
pop = newPop(founderPop, simParam=SP)
meanG(pop)

#Change mean to 1
SP$rescaleTraits(mean=1)
\dontshow{SP$nThreads = 1L}
#Run resetPop for change to take effect
pop = resetPop(pop, simParam=SP)
meanG(pop)

Method setRecombRatio()

Set the relative recombination rates between males and females. This allows for sex-specific recombination rates, under the assumption of equivalent recombination landscapes.

Usage

SimParam$setRecombRatio(femaleRatio)

Arguments

femaleRatio

relative ratio of recombination in females compared to males. A value of 2 indicate twice as much recombination in females. The value must be greater than 0. (default is 1)

Examples

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
\dontshow{SP$nThreads = 1L}
SP$setRecombRatio(2) #Twice as much recombination in females

Method switchGenMap()

Replaces existing genetic map.

Usage

SimParam$switchGenMap(genMap, centromere = NULL)

Arguments

genMap

a list of length nChr containing numeric vectors for the position of each segregating site on a chromosome.

centromere

a numeric vector of centromere positions. If NULL, the centromere are assumed to be metacentric.

Method switchFemaleMap()

Replaces existing female genetic map.

Usage

SimParam$switchFemaleMap(genMap, centromere = NULL)

Arguments

genMap

a list of length nChr containing numeric vectors for the position of each segregating site on a chromosome.

centromere

a numeric vector of centromere positions. If NULL, the centromere are assumed to be metacentric.

Method switchMaleMap()

Replaces existing male genetic map.

Usage

SimParam$switchMaleMap(genMap, centromere = NULL)

Arguments

genMap

a list of length nChr containing numeric vectors for the position of each segregating site on a chromosome.

centromere

a numeric vector of centromere positions. If NULL, the centromere are assumed to be metacentric.

Method addToRec()

For internal use only.

Usage

SimParam$addToRec(lastId, id, mother, father, isDH, hist, ploidy)

Arguments

lastId

ID of last individual

id

the name of each individual

mother

vector of mother iids

father

vector of father iids

isDH

indicator for DH lines

hist

new recombination history

ploidy

ploidy level

Method ibdHaplo()

For internal use only.

Usage

SimParam$ibdHaplo(iid)

Arguments

iid

internal ID

Method updateLastId()

For internal use only.

Usage

SimParam$updateLastId(lastId)

Arguments

lastId

last ID assigned

Method addToPed()

For internal use only.

Usage

SimParam$addToPed(lastId, id, mother, father, isDH)

Arguments

lastId

ID of last individual

id

the name of each individual

mother

vector of mother iids

father

vector of father iids

isDH

indicator for DH lines

Method clone()

The objects of this class are cloneable with this method.

Usage

SimParam$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples


## ------------------------------------------------
## Method `SimParam$new`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)

## ------------------------------------------------
## Method `SimParam$setTrackPed`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$setTrackPed(TRUE)

## ------------------------------------------------
## Method `SimParam$setTrackRec`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$setTrackRec(TRUE)

## ------------------------------------------------
## Method `SimParam$resetPed`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)

#Create population
pop = newPop(founderPop, simParam=SP)
pop@id # 1:10
#>  [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10"

#Create another population after reseting pedigree
SP$resetPed()
pop2 = newPop(founderPop, simParam=SP)
pop2@id # 1:10
#>  [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10"

## ------------------------------------------------
## Method `SimParam$restrSegSites`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$restrSegSites(minQtlPerChr=5, minSnpPerChr=5)

## ------------------------------------------------
## Method `SimParam$setSexes`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$setSexes("yes_sys")

## ------------------------------------------------
## Method `SimParam$addSnpChip`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addSnpChip(10)

## ------------------------------------------------
## Method `SimParam$addSnpChipByName`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addSnpChipByName(c("1_1","1_3"))

## ------------------------------------------------
## Method `SimParam$addTraitA`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10)

## ------------------------------------------------
## Method `SimParam$addTraitAD`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitAD(10, meanDD=0.5)

## ------------------------------------------------
## Method `SimParam$altAddTraitAD`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$altAddTraitAD(nQtlPerChr=10, mean=0, varA=1, varD=0.05, inbrDepr=0.2)
#> A new trait called Trait1 was added. 
#>    varD = 0.05000002 
#>    inbrDepr = 0.2000004 
#>    meanDD = 0.04665813 
#>    varDD = 0.1382312 

## ------------------------------------------------
## Method `SimParam$addTraitAG`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitAG(10, varGxE=2)

## ------------------------------------------------
## Method `SimParam$addTraitADG`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitADG(10, meanDD=0.5, varGxE=2)

## ------------------------------------------------
## Method `SimParam$addTraitAE`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitAE(10, relAA=0.1)

## ------------------------------------------------
## Method `SimParam$addTraitADE`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitADE(10)

## ------------------------------------------------
## Method `SimParam$addTraitAEG`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitAEG(10, varGxE=2)

## ------------------------------------------------
## Method `SimParam$addTraitADEG`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitADEG(10, meanDD=0.5, varGxE=2)

## ------------------------------------------------
## Method `SimParam$setVarE`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10)
SP$setVarE(h2=0.5)

## ------------------------------------------------
## Method `SimParam$setCorE`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10, mean=c(0,0), var=c(1,1), corA=diag(2))
SP$setVarE(varE=c(1,1))
E = 0.5*diag(2)+0.5 #Positively correlated error
SP$setCorE(E)
#> Warning: This function has been deprecated. Use simParam$setVarE instead.

## ------------------------------------------------
## Method `SimParam$rescaleTraits`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$addTraitA(10)

#Create population
pop = newPop(founderPop, simParam=SP)
meanG(pop)
#>        Trait1 
#> -6.661338e-17 

#Change mean to 1
SP$rescaleTraits(mean=1)
#Run resetPop for change to take effect
pop = resetPop(pop, simParam=SP)
meanG(pop)
#> Trait1 
#>      1 

## ------------------------------------------------
## Method `SimParam$setRecombRatio`
## ------------------------------------------------

#Create founder haplotypes
founderPop = quickHaplo(nInd=10, nChr=1, segSites=10)

#Set simulation parameters
SP = SimParam$new(founderPop)
SP$setRecombRatio(2) #Twice as much recombination in females