| MDSMap-package {MDSMap} | R Documentation |
High density Genetic Linkage Mapping using Multidimensional Scaling
Description
MDSmap provides functions for estimating genetic linkage maps for markers from a single linkage group from pairwise intermarker map distances using the Haldane or Kosambi map function; or recombination fractions. It either uses constrained weighted metric multidimensional scaling (cMDS) in 2 dimensions or unconstrained weighted metric multidimensional scaling (MDS) followed by fitting a principal curve (PC) in either 2 or 3 dimensions. Pairwise distances can be weighted either by the LOD score or LOD2. There are functions for diagnostic plots, estimating the difference between the observed and estimated difference between points and their nearest informative neighbour, which may be useful in deciding which weights to use and also for testing estimated maps against a map estimated externally.
Details
The main top level functions to use: calc.maps.pc and
calc.maps.sphere, and use plot.pcmap,
plot.spheremap or plot.pcmap3d to visualize
the result.
Author(s)
Katharine F. Preedy <Katharine.preedy@bioss.ac.uk>
Examples
map<-calc.maps.pc(system.file("extdata", "lgV.txt", package="MDSMap"),
ndim=2,weightfn='lod2',mapfn='kosambi')
plot(map)