geneticPosition {hsrecombi}

Estimation of genetic position

Description

Estimation of genetic positions (in centi Morgan)

Usage

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

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.

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)

References

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

Examples

  ### 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)