For a given sequence with \(n\) markers, computes the multipoint likelihood of all \(\frac{n!}{2}\) possible orders.
compare(input.seq, n.best = 50, tol = 0.001, verbose = FALSE)an object of class sequence.
the number of best orders to store in object (defaults to 50).
tolerance for the C routine, i.e., the value used to evaluate convergence.
if FALSE (default), simplified output is displayed.
if TRUE, detailed output is displayed.
An object of class compare, which is a list containing the
following components:
a matrix containing the best
orders.
a matrix with recombination frequencies
for the corresponding best orders.
a matrix
with linkage phases for the best orders.
a
vector with log-likelihood values for the best orders.
a vector with LOD Score values for the best
orders.
name of the object of class outcross with
the raw data.
name of the object of class rf.2pts with
the 2-point analyses.
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 recomend 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.
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
marker.type for details about segregation
types and make.seq.
# NOT RUN {
# }
# NOT RUN {
#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))
# }
# NOT RUN {
# }
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