[adegenet-forum] Resampling loci from a large genlight

[David Dayan]

Hi all,

I'm looking to sample loci from a single population in a large genlight
object (13850 loci, 872 diploid individuals), and convert this genlight
information to a genind object (to use across other packages/adegenet
functions).

Simulated example (calculating He using the Hs() function from 100 sampled
loci):

> simdata<-glSim(10,500, ploidy=2)
> pop(simdata)<-rep(c("a","b"),5)
> Hs(df2genind(as.data.frame(seppop(simdata)$a[,sample(1:500,
100)]),sep="/t",ploidy=2))

This is problematic because the df2genind(as.data.frame(genlight)) method
doesn't seem to work for diploid data (see below).

>
sim2sampled_genind<-df2genind(as.data.frame(seppop(simdata)$a[,sample(1:500,
100)]),sep="/t",ploidy=2)
> head(sim2sampled_genind at tab)

This produces a genind that stores data as binary and therefore cannot
represent my actual data (diploid + missing data).

I realize that starting from a genind object and using the @tab slot will
solve this, but resampling from a genind this size is exceptionally slow
and my ultimate goal is to work this script into a bootstrapping procedure:

So, (a) any advice on converting genlight to genind for diploid data? or
(b) is there a better way to sample loci for bootstrapping that is
computationally efficient/fast?

Thanks,

David Dayan
Rosenstiel School of Marine and Atmospheric Science
University of Miami
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