从VCF文件中计算不同群体间的Fst值：创建进化树、绘制关系网、进行PCA主成分分析详解
最编程
2024-02-10 13:05:00
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rubi.pca <- glPca(gl.rubi, nf = 3)
barplot(100*rubi.pca$eig/sum(rubi.pca$eig), col = heat.colors(50), main="PCA Eigenvalues")
title(ylab="Percent of variance\nexplained", line = 2)
title(xlab="Eigenvalues", line = 1)
rubi.pca.scores <- as.data.frame(rubi.pca$scores)
rubi.pca.scores$pop <- pop(gl.rubi)
library(ggplot2)
set.seed(9)
p <- ggplot(rubi.pca.scores, aes(x=PC1, y=PC2, colour=pop))
p <- p + geom_point(size=2)
p <- p + stat_ellipse(level = 0.95, size = 1)
p <- p + scale_color_manual(values = cols)
p <- p + geom_hline(yintercept = 0)
p <- p + geom_vline(xintercept = 0)
p <- p + theme_bw()
p
