fillX.G {MasterBayes} | R Documentation

## Mendelian Transition Probalities

### Description

This function is primarily intended for use within `getXlist`, and fills in the design matrices of the model with the genetic likelihoods. The model of genotyping error for codominant markers is taken from CERVUS (Kalinowski, 2006; Marshall, 1998), and the model for dominant markers is taken from (Hadfield, 2007).

### Usage

    fillX.G(X.list, A, G, E1=0.005, E2=0.005, marker.type="MS", ...)

### Arguments

`X.list` | list of design matrices for each offspring derived using `getXlist`
`A` | list of allele frequencies
`G` | list of genotype objects; rows must correspond to individuals in the vector `X.list$id`
`E1` | the probability of a dominant allele being scored as a recessive allele for dominant markers
`E2` | per-allele genotyping error rate. `E2`(2-`E2`) is the per-genotype rate defined in Kalinowski (2006) for codominant markers, and `E2` is the probability of a recessive allele being scored as a dominant allele for dominant markers
`marker.type` | "MS" or "AFLP" for codominant or dominant markers respectively
`...` | further arguments to be passed

### Value

list of design matrices of the form `X.list` containing genetic likelihoods for each offspring.

### Note

If a `GdataPed` object is passed to `getXlist` then the genetic likelihoods will be calculated by default.

### Author(s)

Jarrod Hadfield j.hadfield@sheffield.ac.uk

### References

Kalinowski S.T. et al (2006) Molecular Ecology in press Hadfield J. D. et al (2007) in prep

### See Also

`getXlist`

### Examples

    data(WarblerG)
    A<-extractA(WarblerG)

    ped<-matrix(NA, 5,3)
    ped[,1]<-1:5
    ped[,2]<-c(rep(NA, 4), 1)
    ped[,3]<-c(rep(NA, 4), 2)

    genotypes<-simgenotypes(A, ped=ped)

    sex<-c("Female", "Male", "Female", "Male","Female")
    offspring<-c(0,0,0,0,1)

    data<-data.frame(id=ped[,1], sex, offspring)

    res1<-expression(varPed(x="offspring", restrict=0))

    PdP<-PdataPed(formula=list(res1), data=data)
    GdP<-GdataPed(G=genotypes$Gobs, id=genotypes$id)

    X.list<-getXlist(PdP)
    # creates design matrices for offspring (in this case indivdiual "5")

    X.list.G<-fillX.G(X.list, A=A, G=genotypes$Gobs, E2=0.005)
    # genetic likelihoods are arranged sires within dams

    X.list.G$X$"5"$dam.id
    X.list.G$X$"5"$sire.id

    # so for this example we have parental combinations
    # ("1","2"), ("1","4"), ("3","2"), ("2","4"):

    X.list.G$X$"5"$G

    # The true parents have the highest likelihood in this case

[Package MasterBayes version 2.0 Index]