qtl2: calc_entropy – R documentation

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calc_entropy

Calculate entropy of genotype probability distribution

Description

For each individual at each genomic position, calculate the entropy of the genotype probability distribution, as a quantitative summary of the amount of missing information.

Usage

calc_entropy(probs, quiet = TRUE, cores = 1)

Arguments

`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

We calculate -sum(p log_2 p), where we take 0 log 0 = 0.

Value

A list of matrices (each matrix is a chromosome and is arranged as individuals x markers).

Examples

grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2"))

probs <- calc_genoprob(grav2, error_prob=0.002)
e <- calc_entropy(probs)
e <- do.call("cbind", e) # combine chromosomes into one big matrix

# summarize by individual
mean_ind <- rowMeans(e)

# summarize by marker
mean_marker <- colMeans(e)

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