qtl2: calc_errorlod – R documentation

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calc_errorlod

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 = log10[ Pr(O[k] | g[k] = O[k]) / Pr(O[k] | g[k] != 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.

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)

qtl2

Quantitative Trait Locus Mapping in Experimental Crosses

v0.24

GPL-3

Authors

Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), R Core Team [ctb]

Initial release

2020-12-16