est_map: Estimate genetic maps

In simecek/qtl2: Tools for analyzing high-dimensional QTL experiments

Description

Uses a hidden Markov model to re-estimate the genetic map for an experimental cross, with possible allowance for genotyping errors.

Usage

est_map(cross, error_prob = 0.0001, map_function = c("haldane", "kosambi",
  "c-f", "morgan"), maxit = 10000, tol = 0.000001, quiet = TRUE,
  n_cores = 1)

Arguments

cross	Object of class "cross2". For details, see the R/qtl2 developer guide.
error_prob	Assumed genotyping error probability
map_function	Character string indicating the map function to use to convert genetic distances to recombination fractions.
maxit	Maximum number of iterations in EM algorithm.
tol	Tolerance for determining convergence
quiet	If FALSE, print progress messages.
n_cores	Number of CPU cores to use, for parallel calculations. (If 0, use detectCores.)

Details

The map is estimated assuming no crossover interference, but a map function (by default, Haldane's) is used to derive the genetic distances.

Value

A list of numeric vectors, with the estimated marker locations (in cM). The location of the initial marker on each chromosome is kept the same as in the input cross.

Examples

grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2"))
gmap <- est_map(grav2, error_prob=0.002, n_cores=1)

simecek/qtl2 documentation built on May 29, 2019, 10:01 p.m.