calc_errorlod: Calculate genotyping error LOD scores

In rqtl/qtl2: Quantitative Trait Locus Mapping in Experimental Crosses

Calculate genotyping error LOD scores

Description

Use the genotype probabilities calculated with calc_genoprob() to calculate genotyping error LOD scores, to help identify potential genotyping errors (and problem markers and/or individuals).

Usage

calc_errorlod(cross, probs, quiet = TRUE, cores = 1)

Arguments

cross	Object of class "cross2". For details, see the R/qtl2 developer guide.
probs	Genotype probabilities as calculated from calc_genoprob().
quiet	If FALSE, print progress messages.
cores	Number of CPU cores to use, for parallel calculations. (If 0, use parallel::detectCores().) Alternatively, this can be links to a set of cluster sockets, as produced by parallel::makeCluster().

Details

Let O_k denote the observed marker genotype at position k, and g_k denote the corresponding true underlying genotype.

Following Lincoln and Lander (1992), we calculate LOD = log_{10} [ Pr(O_k | g_k = O_k) / Pr(O_k | g_k \ne O_K) ]

Value

A list of matrices of genotyping error LOD scores. Each matrix corresponds to a chromosome and is arranged as individuals x markers.

References

Lincoln SE, Lander ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604–610.

See Also

calc_genoprob()

Examples

iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2"))
probs <- calc_genoprob(iron, error_prob=0.002, map_function="c-f")
errorlod <- calc_errorlod(iron, probs)

# combine into one matrix
errorlod <- do.call("cbind", errorlod)

rqtl/qtl2 documentation built on March 20, 2024, 6:35 p.m.