I'm using 1000 genome data on European populations. I know there should be some population structure, but smartpca (from eigensoft version 6) gives very different PCs and eigenvalues for each of the 22 chromosomes. By this I mean if I look at the PCA plots, they look very different (some are really separated out by PC1 and 2 whereas others aren't). I have done HWE, missingness, maf>0.01 filtering on this dataset and asked smartpca to remove outliers, so I *think* the data is very well filtered. The only thing I can think of is that the sample size is so small (I'm using 450 samples) that only a few datapoints/informative SNPs from each population is present in each chromosome, and that changes the PCs. Has anyone else had this problem? If so, did you end up doing smartpca on the whole genome? Or what did you use as PCs to correct for population structure?
Question: SmartPCA gives very different PCs for different chromosomes
4.0 years ago by
janeshen91 • 0
janeshen91 • 0 wrote:
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