Description Usage Arguments Details Value See Also Examples
Uses a hidden Markov model to calculate the probabilities of the true underlying genotypes given the observed multipoint marker data, with possible allowance for genotyping errors.
1 2 3 | calc_genoprob(cross, map = NULL, error_prob = 0.0001,
map_function = c("haldane", "kosambi", "c-f", "morgan"), lowmem = FALSE,
quiet = TRUE, cores = 1)
|
cross |
Object of class |
map |
Genetic map of markers. May include pseudomarker
locations (that is, locations that are not within the marker
genotype data). If NULL, the genetic map in |
error_prob |
Assumed genotyping error probability |
map_function |
Character string indicating the map function to use to convert genetic distances to recombination fractions. |
lowmem |
If |
quiet |
If |
cores |
Number of CPU cores to use, for parallel calculations.
(If |
Let O[k] denote the observed marker genotype at position k, and g[k] denote the corresponding true underlying genotype.
We use the forward-backward equations to calculate a[k][v] = log Pr(O[1], …, O[k], g[k] = v) and b[k][v] = log Pr(O[k+1], …, O[n] | g[k] = v)
We then obtain Pr(g[k] | O[1], …, O[n] = exp(a[k][v] + b[k][v]) / s where s = sum_v exp(a[k][v] + b[k][v])
A list of three-dimensional arrays of probabilities, individuals x genotypes x positions. (Note that the arrangement is different from R/qtl.) Also contains four attributes:
crosstype
- The cross type of the input cross
.
is_x_chr
- Logical vector indicating whether chromosomes
are to be treated as the X chromosome or not, from input cross
.
alleles
- Vector of allele codes, from input
cross
.
alleleprobs
- Logical value (FALSE
) that
indicates whether the probabilities are compressed to allele
probabilities, as from genoprob_to_alleleprob()
.
1 2 3 | grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2geno"))
gmap_w_pmar <- insert_pseudomarkers(grav2$gmap, step=1)
probs <- calc_genoprob(grav2, gmap_w_pmar, error_prob=0.002)
|
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