R: Probability of a Genotype.

genoProb {QTLRel} | R Documentation

## Probability of a Genotype.

### Description

Calculate the probability of a genotype at a locus conditional on the genotypes of its flanking markers in advance intercross lines (AIL).

### Usage

    genoProb(gdat, gmap, step = Inf, gr = 2, pos = NULL, method=c("Haldane",
       "Kosambi"), msg = FALSE)

### Arguments

`gdat` | Genotype data. Should be a matrix or a data frame, with each row representing an observation and each column a marker locus. The column names should be marker names. Each entry should be 1, 2, 3 or 0, corresponding to "AA", "AB", "BB" or missing genotype.
`gmap` | A genetic map. Should be data frame (snp, chr, dist,...), where "snp" is the SNP (marker) name, "chr" is the chromosome where the "snp" is, and "dist" is the genetic distance in centi-Morgan (cM) from the left of the chromosome.
`step` | The maximum "cumulative" distance (in cM) between two adjacent loci for which the probabilities are calculated. The distance corresponds to the "cumulative" recombination rate at `gr`-th generation.
`gr` | The generation under consideration.
`pos` | Data frame (chr, dist, snp, ...). If given, `step` will be ignored.
`method` | Whether "Haldane" or "Kosambi" mapping function should be used.
`msg` | A logical variable. If TRUE, certain information will be printed out during calculation.

### Details

The "cumulative" genetic distance between any two adjacent loci for which probabilities are calculated is not larger than `step`. If `step = Inf`, probabilities will only be calculated at loci in both the columns of `gdat` and the rows of `gmap`. If `step` is small, a large set of putative loci will be considered, including all loci defined by the columns of `gdat` and the rows of `gmap`.

### Value

Probabilities for genotypes as well as genetic map information (snp,chr,dist)

`pr` | A 3-D array with the first dimension corresponding to that of `gdat`, the second to three genotype and the third to the putative loci. The probabilities will be -1 if not imputable, which happens when the genotype data is missing at all loci on the chromosome.

### Note

Currently only suitable for advanced intercross lines.

### Examples

    data(miscEx)

    ## Not run:
    # briefly look at genotype data
    sum(is.na(gdatF8))
    gdatF8[1:5,1:5]

    gdtmp<- gdatF8
       gdtmp<- replace(gdtmp,is.na(gdtmp),0)
    # In case an individual is not imputable, then
    # one needs to assign genotypes manually
    prDat<- genoProb(gdat=gdtmp, gmap=gmapF8, step=Inf,
       gr=8, method="Haldane", msg=TRUE)
    prDat$pr[1:5,,1:5]

    ## End(Not run)

[Package QTLRel version 1.0 Index]