mds_mappoly {mappoly}

Estimates loci position using Multidimensional Scaling

Description

Estimates loci position using Multidimensional Scaling proposed by Preedy and Hackett (2016). The code is an adaptation from the package MDSmap, available under GNU GENERAL PUBLIC LICENSE, Version 3, at https://CRAN.R-project.org/package=MDSMap

Usage

mds_mappoly(
  input.mat,
  p = NULL,
  n = NULL,
  ndim = 2,
  weight.exponent = 2,
  verbose = TRUE
)

## S3 method for class 'mappoly.pcmap'
print(x, ...)

## S3 method for class 'mappoly.pcmap3d'
print(x, ...)

Arguments

input.mat

an object of class mappoly.input.matrix

p

integer. The smoothing parameter for the principal curve. If NULL (default) this will be done using the leave-one-out cross validation

n

vector of integers or strings containing loci to be omitted from the analysis

ndim

number of dimensions to be considered in the multidimensional scaling procedure (default = 2)

weight.exponent

the exponent that should be used in the LOD score values to weight the MDS procedure (default = 2)

verbose

if TRUE (default), display information about the analysis

x

an object of class mappoly.mds

...

currently ignored

Value

A list containing:

M

the input distance map

sm

the unconstrained MDS results

pc

the principal curve results

distmap

a matrix of pairwise distances between loci where the columns are in the estimated order

locimap

a data frame of the loci containing the name and position of each locus in order of increasing distance

length

integer giving the total length of the segment

removed

a vector of the names of loci removed from the analysis

scale

the scaling factor from the MDS

locikey

a data frame showing the number associated with each locus name for interpreting the MDS configuration plot

confplotno

a data frame showing locus name associated with each number on the MDS configuration plots

Author(s)

Marcelo Mollinari, [e-mail] mostly adapted from MDSmap codes, written by Katharine F. Preedy, [e-mail]

References

Preedy, K. F., & Hackett, C. A. (2016). A rapid marker ordering approach for high-density genetic linkage maps in experimental autotetraploid populations using multidimensional scaling. _Theoretical and Applied Genetics_, 129(11), 2117-2132. doi:10.1007/s00122-016-2761-8

Examples

    s1 <- make_seq_mappoly(hexafake, 1:20)
    t1 <- est_pairwise_rf(s1, ncpus = 1)
    m1 <- rf_list_to_matrix(t1)
    o1 <- get_genomic_order(s1)
    s.go <- make_seq_mappoly(o1)
    plot(m1, ord = s.go$seq.mrk.names)
    mds.ord <- mds_mappoly(m1)
    plot(mds.ord)
    so <- make_seq_mappoly(mds.ord)
    plot(m1, ord = so$seq.mrk.names)
    plot(so$seq.num ~ I(so$genome.pos/1e6), 
         xlab = "Genome Position",
         ylab = "MDS position")