Forum: question about PCA in plink 1.9
I'm new in biostatistics and I work on something about GWAS with plink.
I used plink 1.9 to do the PCA with the code as following:
plink --bfile data --pca
and get the .eigenval and .eigenvec file.
I think the results of eigenval file (as following)is wired, is that mean the amount of variance accounted for by the principle component? if it is, should I count the percentage variance explained by certain PC divided by total variance? But the percentage is too small.how many eigenvectors should I choose then?
20.0134
2.98845
2.32333
1.94295
1.93421
1.91117
1.88628
1.86544
1.85781
1.84763
1.76204
1.5532
1.3277
1.1808
1.14857
1.13482
1.13316
1.12439
1.1194
1.11312
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summeryhx •
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summeryhx •
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question about PCA in plink 1.9
written by summeryhx •
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