Created
June 17, 2020 05:13
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PlotPCA For Anything - might need some tweaking
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| plotPCA_v2 <- function(x, intgroup = "condition", ntop = 500, col) | |
| { | |
| rv = rowVars(x) | |
| select = order(rv, decreasing = TRUE)[seq_len(min(ntop, length(rv)))] | |
| pca = prcomp(t(x[select, ])) | |
| fac = factor(apply(as.data.frame(colData(x)[, intgroup, drop = FALSE]), | |
| 1, paste, collapse = " : ")) | |
| if (missing(col)) { | |
| col = if (nlevels(fac) >= 3) | |
| brewer.pal(nlevels(fac), "Paired") | |
| else c("lightgreen", "dodgerblue") | |
| } | |
| imp = summary(pca)$importance[2,] | |
| par(mar=c(1,1,1,1)) | |
| xyplot(PC2 ~ PC1, groups = fac, data = as.data.frame(pca$x), | |
| pch = 16, cex = 2, aspect = "iso", col = col, main = draw.key(key = list(rect = list(col = col), | |
| text = list(levels(fac)), rep = FALSE)), xlab = paste('PC1 (',signif(imp[[1]],2)*100,'%)',sep=''), ylab = paste('PC2 (',signif(imp[[2]],2)*100,'%)',sep='')) | |
| } |
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