gscan: Genome scan for hybrids
In AFLPsim: Hybrid Simulation and Genome Scan for Dominant Markers

Description Usage Arguments Details Value Author(s) References See Also Examples

This function fits genomic scan to dominant genotypic data using the method described by Gagnaire et al (2009) and the new method by Balao et al (2013; in preparation). Significance testing for outlier loci is included.

1	gscan(mat, type=c("F1","BxA","BxB"), method=c("bal&gar-ca","gagnaire"))

`mat`	an object of class '`hybridsim`' produced by '`hybridsim`' or '`hybridize`' functions
`type`	the type of hybrid classes; either "F1", "BxA" or "BxB"
`method`	a character string specifying the method to test significance of outlier loci; either "gagnaire" or "bal&gar-ca". See Details.

These genome scan methods calculate the null distribution of frequencies under a neutral model.

Gagnaire's method uses a binomial test to outlier significance. For more conservative and unbiased method, "Bal&gar-car" method calculates the 95% confidence expected hybrid frequencies by the Clopper-Pearson 'exact' procedure (Clopper & Pearson 1934; Brown et al. 2001).

In both methods, the False Discovery Rate (FDR) correction (Benjamini & Hochberg 1995) is used to counteract for multiple comparisons and control the expected proportion of incorrectly rejected null hypotheses.

A list with the following components:

`P-values`	a matrix with P values after False Discovery Rate correction for each loci
`Outlier`	a vector with outliers

F. Balao fbalao@us.es, J.L. García-Castaño

Balao, F. and García-Castaño, J.L. AFLPsim: an R package to simulate and detect dominant markers under selection in hybridizing populations. Plant Methods 10:40

Balao, F., Casimiro-Soriguer, R., García-Castaño, J.L., Terrab, A., Talavera, S. 2013. Big thistle eats the little thistle: Non-neutral unidirectional introgression endangers the conservation of Onopordum hinojense. New Phytologist, in press.

Benjamini, Y., and Y. Hochberg. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B 57: 289-300.

Brown LD, Cai TT, Anirban D (2001) Interval estimation for a binomial proportion. Statistical Science 16: 101-117.

Clopper CJ, Pearson ES (1934) The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26: 404-413

Gagnaire, P.A., V. Albert, B. Jonsson, L. Bernatchez. 2009. Natural selection influences AFLP intraspecific genetic variability and introgression patterns in Atlantic eels. Molecular Ecology 18: 1678-1691.

hybridsim

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hybrids<-hybridsim(Nmarker=100, Na=30, Nb=30, Nf1=30, type="selection", S=5,Nsel=25, hybrid="F1")

outliers<-gscan(hybrids, type="F1", method="bal&gar-ca")