getPCA: Create a principal component analysis (PCA) plot for the...

In PTXQC: Quality Report Generation for MaxQuant and mzTab Results

Create a principal component analysis (PCA) plot for the first two dimensions.

Description

Create a principal component analysis (PCA) plot for the first two dimensions.

Usage

getPCA(data, do_plot = TRUE, connect_line_order = NA, gg_layer)

Arguments

data	Matrix(!) where each row is one high-dimensional point, with ncol dimensions, e.g. a mouse as an array of proteinexpressions rownames(data) give classes for colouring (can be duplicates in matrices, as opposed to data.frames)
do_plot	Show PCA plot? if ==2, then shows correlations plot as well
connect_line_order	Connect points by lines, the order is given by this vector. Default: NA (no lines)
gg_layer	More parameters added to a ggplot object (ggplot(x) + gg_layer)

Value

[invisible] Named list with "PCA": The PCA object as returned by prcomp, access $x for PC values and "plots": list of plot objects (one or two)

PTXQC documentation built on July 26, 2023, 5:27 p.m.