Description Usage Arguments Details Value Examples
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.
1 | calc_entropy(probs, quiet = TRUE, cores = 1)
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probs |
Genotype probabilities, as calculated from
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quiet |
IF |
cores |
Number of CPU cores to use, for parallel calculations.
(If |
We calculate -sum(p log_2 p), where we take 0 log 0 = 0.
A list of matrices (each matrix is a chromosome and is arranged as individuals x markers).
1 2 3 4 5 6 7 8 9 10 | grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2geno"))
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
hist(rowMeans(e), breaks=25, main="Ave entropy by individual", xlab="Entropy")
# summarize by marker
plot(colMeans(e), xlab="marker index", ylab="Average entropy")
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