calc_errorlod: Calculate genotyping error LOD scores
In rqtl/qtl2geno: Treatment of Marker Genotypes for QTL Experiments

Description Usage Arguments Details Value References See Also Examples

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).

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

`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()`.

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]) ]

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

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

calc_genoprob()

iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2geno"))
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)