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Stephen Petersen wrote:<br>
<br>
Dear Stephen, <br>
<blockquote cite="mid:FDELLIBLEJFBGDPJKFMMKELHCLAA.spetersen@nrdpfc.ca"
type="cite">
<pre wrap="">Hello,
I am having trouble as I try to sub sample from a population. I would like
to sub sample after I have created the genind object so that I can separate
populations then randomly pull samples from a specific population.
</pre>
</blockquote>
I am not sure I understand what you want to do, so sorry if I miss the
point. If your purpose is to separate populations from you genind, you
can use seppop:<br>
<tt>##<br>
> data(sim2pop) # sim2pop is a genind with 130 genotypes in two
populations (with 100 and 30 genotypes respectively)<br>
> foo <- seppop(sim2pop)<br>
> foo<br>
<b>$`Pop A`<br>
</b><br>
#####################<br>
### Genind object ### <br>
#####################<br>
- genotypes of individuals - <br>
<br>
S4 class: genind<br>
@call: .local(x = x, i = i, j = j, drop = drop)<br>
<br>
@tab<b>: 100</b> x 241 matrix of genotypes<br>
<br>
@ind.names: vector of 100 individual names<br>
@loc.names: vector of 20 locus names<br>
@loc.nall: number of alleles per locus<br>
@loc.fac: locus factor for the 241 columns of @tab<br>
@all.names: list of 20 components yielding allele names for each locus<br>
@ploidy: 2<br>
<br>
Optionnal contents: <br>
@pop: factor giving the population of each individual<br>
@pop.names: factor giving the population of each individual<br>
<br>
@other: a list containing: xy <br>
<br>
<br>
<b>$`Pop B`</b><br>
<br>
#####################<br>
### Genind object ### <br>
#####################<br>
- genotypes of individuals - <br>
<br>
S4 class: genind<br>
@call: .local(x = x, i = i, j = j, drop = drop)<br>
<br>
@tab: <b>30</b> x 241 matrix of genotypes<br>
<br>
@ind.names: vector of 30 individual names<br>
@loc.names: vector of 20 locus names<br>
@loc.nall: number of alleles per locus<br>
@loc.fac: locus factor for the 241 columns of @tab<br>
@all.names: list of 20 components yielding allele names for each locus<br>
@ploidy: 2<br>
<br>
Optionnal contents: <br>
@pop: factor giving the population of each individual<br>
@pop.names: factor giving the population of each individual<br>
<br>
@other: a list containing: xy <br>
## </tt><br>
<br>
here, foo is a list with two components, which are genind objects
containing the genotypes from population A and B.<br>
Now, if you want to sample randomly, say 10 genotypes from each
population, you can use:<br>
<tt>> mySamp <- lapply(foo, function(x) x[sample(1:nrow(x$tab),
10)])<br>
> mySamp<br>
$`Pop A`<br>
<br>
#####################<br>
### Genind object ### <br>
#####################<br>
- genotypes of individuals - <br>
<br>
S4 class: genind<br>
@call: .local(x = x, i = i, j = j, drop = drop)<br>
<br>
@tab: 10 x 241 matrix of genotypes<br>
<br>
@ind.names: vector of 10 individual names<br>
@loc.names: vector of 20 locus names<br>
@loc.nall: number of alleles per locus<br>
@loc.fac: locus factor for the 241 columns of @tab<br>
@all.names: list of 20 components yielding allele names for each locus<br>
@ploidy: 2<br>
<br>
Optionnal contents: <br>
@pop: factor giving the population of each individual<br>
@pop.names: factor giving the population of each individual<br>
<br>
@other: a list containing: xy <br>
<br>
<br>
$`Pop B`<br>
<br>
#####################<br>
### Genind object ### <br>
#####################<br>
- genotypes of individuals - <br>
<br>
S4 class: genind<br>
@call: .local(x = x, i = i, j = j, drop = drop)<br>
<br>
@tab: 10 x 241 matrix of genotypes<br>
<br>
@ind.names: vector of 10 individual names<br>
@loc.names: vector of 20 locus names<br>
@loc.nall: number of alleles per locus<br>
@loc.fac: locus factor for the 241 columns of @tab<br>
@all.names: list of 20 components yielding allele names for each locus<br>
@ploidy: 2<br>
<br>
Optionnal contents: <br>
@pop: factor giving the population of each individual<br>
@pop.names: factor giving the population of each individual<br>
<br>
@other: a list containing: xy <br>
## <br>
<br>
mySamp is a list with 2 genind objects, each containing 10 genotypes
taken at random from populations A and B.<br>
You can put these samples back into a single genind object by using
pool:<br>
> x <- repool(mySamp)<br>
> x<br>
<br>
#####################<br>
### Genind object ### <br>
#####################<br>
- genotypes of individuals - <br>
<br>
S4 class: genind<br>
@call: repool(mySamp)<br>
<br>
@tab: 20 x 175 matrix of genotypes<br>
<br>
@ind.names: vector of 20 individual names<br>
@loc.names: vector of 20 locus names<br>
@loc.nall: number of alleles per locus<br>
@loc.fac: locus factor for the 175 columns of @tab<br>
@all.names: list of 20 components yielding allele names for each locus<br>
@ploidy: 2<br>
<br>
Optionnal contents: <br>
@pop: factor giving the population of each individual<br>
@pop.names: factor giving the population of each individual<br>
<br>
@other: - empty -<br>
<br>
> x$pop<br>
[1] P1 P1 P1 P1 P1 P1 P1 P1 P1 P1 P2 P2 P2 P2 P2 P2 P2 P2 P2 P2<br>
Levels: P1 P2<br>
##<br>
</tt><br>
x contains 20 genotypes randomly drawn from populations A and B.<br>
<br>
<blockquote cite="mid:FDELLIBLEJFBGDPJKFMMKELHCLAA.spetersen@nrdpfc.ca"
type="cite">
<pre wrap="">I'm not sure if am on the correct track but I am able to sample the names
(indlist <- sample(data$ind.names, 5, replace = FALSE, prob = NULL) from my
population but I can't seem to sample the alleles (data$tab ?) or the entire
record for a set of individuals.
</pre>
</blockquote>
The simplest way to subset a genind object is using the [] operator:<br>
x[ ind, all] where 'ind' is the index of individuals kept, and 'all' is
the index of alleles kept. Like in matrices, when nothing is given, all
is kept. For instance: <br>
##<br>
<tt>x[1:5]</tt><br>
##<br>
contains only the 5 first genotypes in x, with all alleles. You can
also use the argument loc="..." to specify loci to be retainde (...
will be a vector naming the retained loci).For instance :<br>
##<br>
<tt>x[1:5, loc="L03"]</tt><br>
##<br>
<br>
contains the 5 first genotypes of x, but only for locus 3.<br>
<br>
<blockquote cite="mid:FDELLIBLEJFBGDPJKFMMKELHCLAA.spetersen@nrdpfc.ca"
type="cite">
<pre wrap="">Any help will be appreciated
Thanks
Stephen
</pre>
</blockquote>
Please have a look at the data manipulation section from the adegenet
tutorial (starting p.10):<br>
<a class="moz-txt-link-freetext" href="http://adegenet.r-forge.r-project.org/files/tutorial.pdf">http://adegenet.r-forge.r-project.org/files/tutorial.pdf</a><br>
which covers these topics.<br>
<br>
Best regards, <br>
<br>
Thibaut.<br>
<blockquote cite="mid:FDELLIBLEJFBGDPJKFMMKELHCLAA.spetersen@nrdpfc.ca"
type="cite">
<pre wrap="">Stephen D. Petersen, Ph.D.
Post Doctoral Researcher
Fisheries & Oceans Canada, ArcticNet
Winnipeg, Manitoba
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</pre>
</blockquote>
<br>
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<br>
Dr Thibaut JOMBART <br>
CNRS UMR 5558 - Laboratoire de Biométrie et Biologie Evolutive <br>
Universite Lyon 1 <br>
43 bd du 11 novembre 1918 <br>
69622 Villeurbanne Cedex <br>
Tél. : 04.72.43.29.35 <br>
Fax : 04.72.43.13.88 <br>
<a class="moz-txt-link-abbreviated" href="mailto:jombart@biomserv.univ-lyon1.fr">jombart@biomserv.univ-lyon1.fr</a> <br>
<a href="http://biomserv.univ-lyon1.fr/%7Ejombart/">http://biomserv.univ-lyon1.fr/%7Ejombart/</a><br>
<a href="http://adegenet.r-forge.r-project.org/">http://adegenet.r-forge.r-project.org/</a><br>
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