How to do pca plot from .eigenvec files from Plink in R

Question

[anithanagaraj93]

I created eigenvec from plink from 8 samples got the following data,

AEBAN1 AEBAN1 0.233739 -0.462444 0.0588818 0.761738 0.141378 0.011553 0.00395623 -0.3573

AEBAN2 AEBAN2 0.227559 -0.0351801 -0.156163 -0.385497 0.814224 -0.0290638 0.00406695 -0.331907

AEBAN3 AEBAN3 -0.451765 0.0376304 0.00883375 0.015282 -0.0234585 -0.619909 -0.538497 -0.345493

AEBAN4 AEBAN4 -0.437627 0.0529541 0.00309719 -0.00807711 0.00933802 0.772843 -0.297348 -0.346142

AEBAN5 AEBAN5 0.225645 -0.412089 -0.526555 -0.355258 -0.496482 0.00371485 0.011119 -0.359398

AEBAN6 AEBAN6 -0.485645 0.0443476 0.012694 0.0095609 -0.00710413 -0.131822 0.788241 -0.350968

AECHN1 AECHN1 0.358227 0.779759 -0.2212 0.234503 -0.149197 -0.00757617 0.00995189 -0.370556

AECHN2 AECHN2 0.287892 -0.0296534 0.803559 -0.299262 -0.218194 -0.000227609 0.00513988 -0.365155

eigenvalue: 0.968773 0.727803 0.683851 0.660557 0.649325 0.427786 0.318728 -0.509643

Then by using the above data how to create PCA plots?

[4galaxy77]

Read this How to do pca plot from .eigenval and .eigenvec files from Plink in R.

[anithanagaraj93]

I tried to create PCA by using below R script

eigen <- data.frame(read.table("plink.eigenvec", header=FALSE, skip=0, sep=" ")) rownames(eigen) <- eigen[,2] eigen <- eigen[,3:ncol(eigen)] summary(eigen) proportionvariances <- ((apply(eigen, 1, sd)^2) / (sum(apply(eigen, 1, sd)^2)))*100 plot(eigen[,1], eigen[,2])

How to add colors to samples after this script?