onemap (version 3.0.0)

compare: Compare all possible orders (exhaustive search) for a given sequence of markers

Description

For a given sequence with \(n\) markers, computes the multipoint likelihood of all \(\frac{n!}{2}\) possible orders.

Usage

compare(input.seq, n.best = 50, tol = 0.001, verbose = FALSE)

Value

An object of class compare, which is a list containing the following components:

best.ord

a matrix containing the best orders.

best.ord.rf

a matrix with recombination frequencies for the corresponding best orders.

best.ord.phase

a matrix with linkage phases for the best orders.

best.ord.like

a vector with log-likelihood values for the best orders.

best.ord.LOD

a vector with LOD Score values for the best orders.

data.name

name of the object of class onemap with the raw data.

twopt

name of the object of class rf_2pts with the 2-point analyses.

Arguments

input.seq

an object of class sequence.

n.best

the number of best orders to store in object (defaults to 50).

tol

tolerance for the C routine, i.e., the value used to evaluate convergence.

verbose

if FALSE (default), simplified output is displayed. if TRUE, detailed output is displayed.

Author

Marcelo Mollinari,

Details

Since the number \(\frac{n!}{2}\) is large even for moderate values of \(n\), this function is to be used only for sequences with relatively few markers. If markers were genotyped in an outcross population, linkage phases need to be estimated and therefore more states need to be visited in the Markov chain; when segregation types are D1, D2 and C, computation can required a very long time (specially when markers linked in repulsion are involved), so we recommend to use this function up to 6 or 7 markers. For inbred-based populations, up to 10 or 11 markers can be ordered with this function, since linkage phase are known. The multipoint likelihood is calculated according to Wu et al. (2002b) (Eqs. 7a to 11), assuming that the recombination fraction is the same in both parents. Hidden Markov chain codes adapted from Broman et al. (2008) were used.

References

Broman, K. W., Wu, H., Churchill, G., Sen, S., Yandell, B. (2008) qtl: Tools for analyzing QTL experiments R package version 1.09-43

Jiang, C. and Zeng, Z.-B. (1997). Mapping quantitative trait loci with dominant and missing markers in various crosses from two inbred lines. Genetica 101: 47-58.

Lander, E. S., Green, P., Abrahamson, J., Barlow, A., Daly, M. J., Lincoln, S. E. and Newburg, L. (1987) MAPMAKER: An interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1: 174-181.

Mollinari, M., Margarido, G. R. A., Vencovsky, R. and Garcia, A. A. F. (2009) Evaluation of algorithms used to order markers on genetics maps. _Heredity_ 103: 494-502.

Wu, R., Ma, C.-X., Painter, I. and Zeng, Z.-B. (2002a) Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing species. Theoretical Population Biology 61: 349-363.

Wu, R., Ma, C.-X., Wu, S. S. and Zeng, Z.-B. (2002b). Linkage mapping of sex-specific differences. Genetical Research 79: 85-96

See Also

marker_type for details about segregation types and make_seq.

Examples

# \donttest{
  #outcrossing example
  data(onemap_example_out)
  twopt <- rf_2pts(onemap_example_out)
  markers <- make_seq(twopt,c(12,14,15,26,28))
  (markers.comp <- compare(markers))
  (markers.comp <- compare(markers,verbose=TRUE))

  #F2 example
  data(onemap_example_f2)
  twopt <- rf_2pts(onemap_example_f2)
  markers <- make_seq(twopt,c(17,26,29,30,44,46,55))
  (markers.comp <- compare(markers))
  (markers.comp <- compare(markers,verbose=TRUE))

# }