calc_genoprob_one_parentR Documentation

Compute conditional probabilities of the genotype (one informative parent)

Description

Conditional genotype probabilities are calculated for each marker position and each individual given a map

Usage

calc_genoprob_one_parent(
  input.map,
  step = 0,
  info.parent = 1,
  uninfo.parent = 2,
  global.err = 0,
  phase.config = "best",
  verbose = TRUE
)

Arguments

input.map

An object of class mappoly.map (with exceptions)

step

Maximum distance (in cM) between positions at which the genotype probabilities are calculated, though for step = 0, probabilities are calculated only at the marker locations.

info.parent

index for informative parent

uninfo.parent

index for uninformative parent

global.err

the assumed global error rate (default = 0.0)

phase.config

which phase configuration should be used. "best" (default) will choose the phase configuration associated with the maximum likelihood

verbose

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

Value

An object of class 'mappoly.genoprob' which has two elements: a tridimensional array containing the probabilities of all possible genotypes for each individual in each marker position; and the marker sequence with it's recombination frequencies

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,stage=build]{tools:::Rd_expr_doi("10.1534/g3.119.400378")}

Examples

 ## tetraploid example
 map <- solcap.dose.map[[1]]
 s <- make_seq_mappoly(map)
 map1 <- est_rf_hmm_single_one_parent(input.seq = s, 
                                      input.ph.single = map$maps[[1]]$seq.ph,
                                      info.parent = 1, 
                                      uninfo.parent = 2, 
                                      tol = 10e-4)
 plot(map1)                                     
 probs <- calc_genoprob_one_parent(input.map = map1, 
                                   info.parent = 1, 
                                   uninfo.parent = 2, 
                                   step = 1)
 probs
 ## displaying individual 1, 6 genotypic states
 ## (rows) across linkage group 1 (columns)                          
 image(t(probs$probs[,,2]))