Function to identify loci under selection per population using the outflank method of Whitlock and Lotterhos (2015)
Function to identify loci under selection per population using the outflank method of Whitlock and Lotterhos (2015)
gl.outflank( gi, plot = TRUE, LeftTrimFraction = 0.05, RightTrimFraction = 0.05, Hmin = 0.1, qthreshold = 0.05, ... )
gi |
a genlight of genind object, with a defined population structure |
plot |
a switch if a barplot is wanted. |
LeftTrimFraction |
The proportion of loci that are trimmed from the lower end of the range of Fst before the likelihood funciton is applied. |
RightTrimFraction |
The proportion of loci that are trimmed from the upper end of the range of Fst before the likelihood funciton is applied. |
Hmin |
The minimum heterozygosity required before including calculations from a locus. |
qthreshold |
The desired false discovery rate threshold for calculating q-values. |
... |
additional parameters (see documentation of outflank on github) |
this function is a wrapper around the outflank function provided by Whitlock and Lotterhus. To be able to run this function the packages qvalue (from bioconductor) and outflank (from github) needs to be installed. To do so see example below.
returns an index of outliers and the full outflank list
Whitlock, M.C. and Lotterhos K.J. (2015) Reliable detection of loci responsible for local adaptation: inference of a neutral model through trimming the distribution of Fst. The American Naturalist 186: 24 - 36.
Github repository: Whitlock & Lotterhos: https://github.com/whitlock/OutFLANK (Check the readme.pdf within the repository for an explanation. Be aware you now can run OufFLANK from a genlight object)
gl.outflank(bandicoot.gl, plot = TRUE)
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