est_full_hmm_with_global_error: Re-estimate genetic map given a global genotyping error

View source: R/reest_map_error.R

est_full_hmm_with_global_errorR Documentation

Re-estimate genetic map given a global genotyping error

Description

This function considers a global error when re-estimating a genetic map using Hidden Markov models. Since this function uses the whole transition space in the HMM, its computation can take a while, especially for hexaploid maps.

Usage

est_full_hmm_with_global_error(
  input.map,
  error = NULL,
  tol = 0.001,
  restricted = TRUE,
  th.prob = 0.95,
  verbose = FALSE
)

Arguments

input.map

an object of class mappoly.map

error

the assumed global error rate (default = NULL)

tol

the desired accuracy (default = 10e-04)

restricted

if TRUE (default), restricts the prior to the possible classes under Mendelian, non double-reduced segregation given dosage of the parents

th.prob

the threshold for using global error or genotype probability distribution if present in the dataset (default = 0.95)

verbose

if TRUE, current progress is shown; if FALSE (default), no output is produced

Value

A list of class mappoly.map with two elements:

i) info: a list containing information about the map, regardless of the linkage phase configuration:

ploidy

the ploidy level

n.mrk

number of markers

seq.num

a vector containing the (ordered) indices of markers in the map, according to the input file

mrk.names

the names of markers in the map

seq.dose.p1

a vector containing the dosage in parent 1 for all markers in the map

seq.dose.p2

a vector containing the dosage in parent 2 for all markers in the map

chrom

a vector indicating the sequence (usually chromosome) each marker belongs as informed in the input file. If not available, chrom = NULL

genome.pos

physical position (usually in megabase) of the markers into the sequence

seq.ref

reference base used for each marker (i.e. A, T, C, G). If not available, seq.ref = NULL

seq.alt

alternative base used for each marker (i.e. A, T, C, G). If not available, seq.ref = NULL

chisq.pval

a vector containing p-values of the chi-squared test of Mendelian segregation for all markers in the map

data.name

name of the dataset of class mappoly.data

ph.thres

the LOD threshold used to define the linkage phase configurations to test

ii) a list of maps with possible linkage phase configuration. Each map in the list is also a list containing

seq.num

a vector containing the (ordered) indices of markers in the map, according to the input file

seq.rf

a vector of size (n.mrk - 1) containing a sequence of recombination fraction between the adjacent markers in the map

seq.ph

linkage phase configuration for all markers in both parents

loglike

the hmm-based multipoint likelihood

Author(s)

Marcelo Mollinari, mmollin@ncsu.edu

References

Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/g3.119.400378")}

Examples

    submap <- get_submap(solcap.dose.map[[1]], mrk.pos = 1:20, verbose = FALSE)
    err.submap <- est_full_hmm_with_global_error(submap, 
                                                 error = 0.01, 
                                                 tol = 10e-4, 
                                                 verbose = TRUE)
    err.submap
    plot_map_list(list(dose = submap, err = err.submap), 
                  title = "estimation procedure")


mmollina/MAPPoly documentation built on March 8, 2024, 2:04 a.m.