simgenotypes {MasterBayes}R Documentation

Genotype and Genotyping Error Simulation

Description

Simulates genotypes given a pedigree and allele frequencies. Option exists to simulate observed genotypes given Wangs's (2004) model of genotyping error for codominat markers or an asymmetric allele based model for dominant markers (Hadfield, 2007).

Usage

simgenotypes(A, E1 = 0, E2 = 0, pedigree, no_dup = 1, prop.missing=0, marker.type="MS", ...)

Arguments

A list of allele frequencies at each locus
E1 Allelic Dropout Rate for codominat markers. Probability of mis-scoring a dominant allele as recessive for dominant markers
E2 Stochastic Error Rate for codominat markers. Probability of mis-scoring a recessive allele as dominant for dominant markers
pedigree pedigree in 3 columns: id, dam, sire. Base individuals have NA as parents. All parents must be in id, and each indivdiual must either have both parents in id, or both parents as base.
no_dup integer: number of times genotypes are to be observed
prop.missing proportion of observed genotypes that are missing
marker.type "MS" or "AFLP" for codominant or dominant markers respectively
... Further arguments to be passed

Value

G list of genotype objects; true genotypes for each locus
Gid vector of id names indexing G
Gobs list of genotype objects; observed genotypes for each locus
id vector of id names indexing Gobs

Author(s)

Jarrod Hadfield j.hadfield@ed.ac.uk

References

Wang J.L. 2004 Genetics 166 4 1963-1979 Hadfield J.D. 2007 in prep

See Also

genotype

Examples

pedigree<-cbind(1:10, rep(NA,10), rep(NA, 10))

gen_data<-simgenotypes(A=list(loc_1=c(0.5, 0.2, 0.1, 0.075, 0.025)), 
 E1=0.1, E2=0.1, pedigree=pedigree, no_dup=1)

summary(gen_data$G[[1]])
summary(gen_data$Gobs[[1]])

[Package MasterBayes version 2.42 Index]