get_pca: Perfors PCA analysis

In kuppal2/xmsPANDA: R Package for Biomarker Discovery, Network, and Data Exploratory Analysis

Description

This function uses the pca function implemented in the mixOmics package for PCA analysis

Usage

get_pca(X, samplelabels, legendlocation = "topright", filename = NA, 
ncomp = 5, center = TRUE, scale = TRUE, legendcex = 0.5, 
outloc = getwd(), col_vec = NA, sample.col.opt = "default", 
alphacol = 0.3, class_levels = NA, pca.cex.val = 3,
pca.ellipse = TRUE, ellipse.conf.level = 0.5, samplenames = FALSE)

Arguments

X	Data matrix without m/z and time.
samplelabels	Vector with class label for each sample.
legendlocation	Location of the legend on PCA score plots
filename	eg: "all", "signficantfeats"
ncomp	Number of components; please use ?pca for more information
center	Should the data be centered?; please use ?pca for more information
scale	Should the data be scaled?; please use ?pca for more information
legendcex	Size of the legend text in the PCA score plots. e.g.: 0.5 or 0.7
outloc	Output folder location
col_vec	Provide vector of colors for each group. eg: NA or c("red","green") for cases and controls, respectively. This argument is ignored if sample.col.opt is provided
sample.col.opt	Select R color palette. eg: "rainbow", "terrain", "topo". "heat", "default"
alphacol	Semi-transparent colors eg: 0.2
class_levels	Vector with names of different sample groups. eg: c("case", "control") or NA
pca.cex.val	Size of dots in PCA score plots. eg: 0.4
pca.ellipse	Should the score confidence interval for each group be drawn? eg: TRUE or FALSE
ellipse.conf.level	Confidence interval level eg: 0.95
samplenames	Should the sample names be included in PCA plots? eg: TRUE or FALSE

Details

This function performs PCA analysis. The results are saved in a RDA file.

Value

The function returns PCA results as an object and generates pairwise score plots for the first three components

Author(s)

Karan Uppal

References

mixOmics

kuppal2/xmsPANDA documentation built on May 15, 2021, 5:48 a.m.