plot_pca: Generate a PCA plot from a gene expression matrix

In jzsh2000/jzshr: jzsh2000's R Code

Description

This function is able to log transform (use rlog function in DESeq2 package) count data originated from a RNA-seq experiment, and draw a PCA plot to reflect sample relationship. That's a good way to check batch effect from gene expression matrix.

Usage

plot_pca(count, color, shape, color.legend = "cell", shape.legend = "donor")

Arguments

count	the gene expression count matrix
color	a character vector whose length is same as samples, different value corresponds to different point color in the plot
shape	a character vector whose length is same as samples, different value corresponds to different point shape in the plot
color.legend	the legend text corresponds to point color
shape.legend	the legend text corresponds to point shape

Value

a ggplot object

Examples

count = matrix(rpois(400, 101:140), 100, 4)
colnames(count) <- paste("sample", 1:4, sep="_")
rownames(count) <- paste("gene", 1:100, sep="_")
plot_pca(count, rep(c('c1','c2'), 2), rep(c('d1', 'd2'), each=2))

jzsh2000/jzshr documentation built on May 20, 2019, 6:29 a.m.