[adegenet-forum] PCA sensitive to order of samples?

[zuzmus]

Dear colleagues,

I would like to perform the PCA in adegenet package and managed to go
through the procedure till the end. The problem is that the results don't
make sense and I see an obvious bias towards the order of the samples in
the input matrix.

The matrix has 140 samples from 11 putative species and cca 2800 SNPs
coming from the RAD-seq method (only biallelicm SNPs included; coded 0 -
more frequent allele, 1 - heterozygote, 2 - rarer allele, NA - missing
data).

I used the following code:

> data <-
read.table("/Users/zuzana/Matrix_for_adegenet_cutSNPsTo2484_NoHybrids.txt")
> x <- new("genlight", data)
> pca1 <- glPca(x)
> scatter(pca1, posi="bottomleft")

The results always show first 5-7 individuals as strongly separated along
the PC1 and 2 and the rest forms one cluster. When I repeated the same
analysis after removing the first few individual from the matrix, the
pattern stayed as it was - the new first individuals became separated.

[image: Vložený obrázek 1]

I also tried to play with most of the options for glPca command following
the manual or help in R, but always got the similar results...

Another issue is that I have quite some missing data (10 - 35 % per SNP,
and cca 10 - 50% per individual) in my matrix, but this was the trade off
of the experiment design ("sequence as much as possible as cheap as
possible..."). But the first individuals in the list are quite well
sequenced, so they are not the worst in sense of missing data...

I wonder if I missed some basics, if I did something wrong or if it is
possible that there really is a bias of the order of the samples in the
matrix? I would be very happy if somebody could help me to find out how to
solve this issue.

Thank you very much of any help and suggestion!:-)

With regards,

Zuzana

---
Zuzana Musilova, PhD.
Zoological Institute
University of Basel
Vesalgasse 1 | 4051 Basel
Switzerland | Europe
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