Thank you, really :)
Hi, I'm working with SNP Array data and after performing a PCA I ended up with two clusters in the same population. Since it's clear this division is showing two different genotyping plates, I would like to find out which SNPs are causing this situation. Do you have any suggestion?
On the other hand, have you ever found situations like this, and if so how did you manage it?
Thanks a lot
1 answer
these are called the "loadings"
> loadings<-snpgdsPCASNPLoading(PCA,genofile)
SNP loading:
Working space: 3893 samples, 3869 SNPs
Using 1 (CPU) core.
Using the top 2 eigenvectors.
SNP Loading: the sum of all working genotypes (0, 1 and 2) = 256360
SNP Loading: Mon Jun 6 11:46:16 2016 0%
SNP Loading: Mon Jun 6 11:46:16 2016 100%
> str(loadings)
List of 8
$ sample.id : chr [1:3893] "AF346967.1" "AF346968.1" "AF346969.1" "AF346976.1" ...
$ snp.id : chr [1:3869] "A10005G" "A10018G" "A10032G" "A10039G" ...
$ eigenval : num [1:3893] 45.1 42.3 NaN NaN NaN ...
$ snploading: num [1:2, 1:3869] -0.008308 -0.000411 0.000923 0.001307 0.001924 ...
$ TraceXTX : num 29776992
$ Bayesian : logi FALSE
$ avefreq : num [1:3869] 0.001027 0.000257 0.000771 0.001027 0.001027 ...
$ scale : num [1:3869] 44.1 88.2 51 44.1 44.1 ...
- attr(*, "class")= chr "snpgdsPCASNPLoadingClass"
I'm sorry. This is my first time doing this kind of analysis, and I'm still having trouble on how to do this. I've tried looking all over. How can I extract the loadings for the PC that I want with its associated snp.id? And how is this different from the snp correlation analysis from this tutorial? Any help will be welcomed!
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