R: Pairwise two-point analysis

est_pairwise_rf

R Documentation

Pairwise two-point analysis

Description

Performs the two-point pairwise analysis between all markers in a sequence. For each pair, the function estimates the recombination fraction for all possible linkage phase configurations and associated LOD Scores.

Usage

est_pairwise_rf(
  input.seq,
  count.cache = NULL,
  count.matrix = NULL,
  ncpus = 1L,
  mrk.pairs = NULL,
  n.batches = 1L,
  est.type = c("disc", "prob"),
  verbose = TRUE,
  memory.warning = TRUE,
  parallelization.type = c("PSOCK", "FORK"),
  tol = .Machine$double.eps^0.25,
  ll = FALSE
)

Arguments

`input.seq`	an object of class `mappoly.sequence`
`count.cache`	an object of class `cache.info` containing pre-computed genotype frequencies, obtained with `cache_counts_twopt`. If `NULL` (default), genotype frequencies are internally loaded.
`count.matrix`	similar to `count.cache`, but in matrix format. Mostly for internal use.
`ncpus`	Number of parallel processes (cores) to spawn (default = 1)
`mrk.pairs`	a matrix of dimensions 2*N, containing N pairs of markers to be analyzed. If `NULL` (default), all pairs are considered
`n.batches`	deprecated. Not available on MAPpoly 0.3.0 or higher
`est.type`	Indicates whether to use the discrete ("disc") or the probabilistic ("prob") dosage scoring when estimating the two-point recombination fractions.
`verbose`	If `TRUE` (default), current progress is shown; if `FALSE`, no output is produced
`memory.warning`	if `TRUE`, prints a memory warning if the number of markers is greater than 10000 for ploidy levels up to 4, and 3000 for ploidy levels > 4.
`parallelization.type`	one of the supported cluster types. This should be either PSOCK (default) or FORK.
`tol`	the desired accuracy. See `optimize()` for details
`ll`	will return log-likelihood instead of LOD scores. (for internal use)

Value

An object of class mappoly.twopt which is a list containing the following components:

`data.name`	name of the object of class `mappoly.data` with the raw data
`n.mrk`	number of markers in the sequence
`seq.num`	a `vector` containing the (ordered) indices of markers in the sequence, according to the input file
`pairwise`	a list of size `choose(length(input.seq$seq.num), 2)`, each of them containing a matrix where the name of the rows have the form x-y, where x and y indicate how many homologues share the same allelic variant in parents P and Q, respectively (see Mollinari and Garcia, 2019 for notation). The first column indicates the LOD Score in relation to the most likely linkage phase configuration. The second column shows the estimated recombination fraction for each configuration, and the third indicates the LOD Score comparing the likelihood under no linkage (r = 0.5) with the estimated recombination fraction (evidence of linkage).

chisq.pval.thresthreshold used to perform the segregation tests chisq.pvalp-values associated with the performed segregation tests

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 (first 50 markers) 
  all.mrk <- make_seq_mappoly(tetra.solcap, 1:50)
  red.mrk <- elim_redundant(all.mrk)
  unique.mrks <- make_seq_mappoly(red.mrk)
  all.pairs <- est_pairwise_rf(input.seq = unique.mrks,
                               ncpus = 1, 
                               verbose = TRUE)
   all.pairs
   plot(all.pairs, 20, 21)
   mat <- rf_list_to_matrix(all.pairs)
   plot(mat)