Learn R Programming

onemap (version 2.0-1)

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 $\frac{n!}{2}$ orders.

Usage

compare(input.seq,n.best=50,tol=10E-4,verbose=FALSE)

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.

Value

  • An object of class compare, which is a list containing the following components:
  • best.orda matrix containing the best orders.
  • best.ord.rfa matrix with recombination frequencies for the corresponding best orders.
  • best.ord.phasea matrix with linkage phases for the best orders.
  • best.ord.likea vector with log-likelihood values for the best orders.
  • best.ord.LODa vector with LOD Score values for the best orders.
  • data.namename of the object of class outcross with the raw data.
  • twoptname of the object of class rf.2pts with the 2-point analyses.

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 of types D1, D2 and C (specially in repulsion phase) are mixed in the sequence, this function can be used with up to 5 or 6 markers; otherwise, up to 10 markers will not take a very long time. 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. For backcross, $F_2$ and RIL populations the linkage phases are known a priori and are not calculated.

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

Run this code
#outcrossing example
  data(example.out)
  twopt <- rf.2pts(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(fake.f2.onemap)
  twopt <- rf.2pts(fake.f2.onemap)
  markers <- make.seq(twopt,c(17,26,29,30,44,46,55)) 
  (markers.comp <- compare(markers))
  (markers.comp <- compare(markers,verbose=TRUE))

Run the code above in your browser using DataLab