geneticPosition: Estimation of genetic position

Description

Estimation of genetic positions (in centi Morgan)

Usage

geneticPosition(final, map1, exclude = NULL, threshold = 0.05)

Value

list (LEN 2)

gen.cM: vector (LEN p) of genetic positions of SNPs (in cM)
gen.Mb: vector (LEN p) of physical positions of SNPs (in Mbp)

Arguments

final

table of results produced by editraw with pairwise estimates of recombination rate between p SNPs within chromosome; minimum required data frame with columns SNP1, SNP2 and theta

map1

data.frame containing information on physical map, at least:

SNP: SNP ID

locus_Mb

physical position in Mbp of SNP on chromosomes

Chr

chromosome of SNP

exclude

optional vector (LEN < p) of SNP IDs to be excluded (e.g., candidates of misplaced SNPs; default NULL)

threshold

optional value; recombination rates <= threshold are considered for smoothing approach assuming theta ~ Morgan (default 0.05)

Details

Smoothing of recombination rates (theta) <= 0.05 via quadratic optimization provides an approximation of genetic distances (in Morgan) between SNPs. The cumulative sum * 100 yields the genetic positions in cM.

The minimization problem (theta - D d)^2 is solved s.t. d > 0 where d is the vector of genetic distances between adjacent markers but theta is not restricted to adjacent markers. The incidence matrix D contains 1's for those intervals contributing to the total distance relevant for each theta.

Estimates of theta = 1e-6 are neglected as these values coincide with start values and indicate that (because of a very flat likelihood surface) no meaningful estimate of recombination rate has been obtained.

References

Qanbari, S. & Wittenburg, D. (2020) Male recombination map of the autosomal genome in German Holstein. Genetics Selection Evolution 52:73. tools:::Rd_expr_doi("10.1186/s12711-020-00593-z")

Examples

Run this code

  ### test data
  data(targetregion)
  ### make list for paternal half-sib families
  hap <- makehaplist(daughterSire, hapSire)
  ### parameter estimates on a chromosome
  res <- hsrecombi(hap, genotype.chr)
  ### post-processing to achieve final and valid set of estimates
  final <- editraw(res, map.chr)
  ### approximation of genetic positions
  pos <- geneticPosition(final, map.chr)

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