calc_genoprob_fst: Calculate conditional genotype probabilities and write to fst database

Description

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.

Usage

calc_genoprob_fst(
  cross,
  fbase,
  fdir = ".",
  map = NULL,
  error_prob = 0.0001,
  map_function = c("haldane", "kosambi", "c-f", "morgan"),
  lowmem = FALSE,
  quiet = TRUE,
  cores = 1,
  compress = 0,
  overwrite = FALSE
)

Value

A list containing the attributes of genoprob

and the address for the created fst database. Components are:

dim - List of all dimensions of 3-D arrays.
dimnames - List of all dimension names of 3-D arrays.
is_x_chr - Vector of all is_x_chr attributes.
chr - Vector of (subset of) chromosome names for this object.
ind - Vector of (subset of) individual names for this object.
mar - Vector of (subset of) marker names for this object.
fst - Path and base of file names for the fst database.

Arguments

cross: Object of class "cross2". For details, see the R/qtl2 developer guide.
fbase: Base of filename for fst database.
fdir: Directory for fst database.
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 cross is used.
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 FALSE, split individuals into groups with common sex and crossinfo and then precalculate the transition matrices for a chromosome; potentially a lot faster but using more memory.
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().
compress: Amount of compression to use (value in the range 0-100; lower values mean larger file sizes)
overwrite: If FALSE (the default), refuse to overwrite any files that already exist.

Details

This is like calling qtl2::calc_genoprob() and then fst_genoprob(), but in a way that hopefully saves memory by doing it one chromosome at a time.

Examples

Run this code

library(qtl2)
grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2"))
gmap_w_pmar <- insert_pseudomarkers(grav2$gmap, step=1)
fst_dir <- file.path(tempdir(), "grav2_genoprob")
dir.create(fst_dir)
probs_fst <- calc_genoprob_fst(grav2, "grav2", fst_dir, gmap_w_pmar, error_prob=0.002)

# clean up: remove all the files we created
unlink(fst_files(probs_fst))