QC_PCA: Principal Component Analysis

In MWASTools: MWASTools: an integrated pipeline to perform metabolome-wide association studies

Description

This function performs PCA on a matrix of metabolic data and returns the results as an object of class "prcomp". When quality control (QC) samples are available, "QC_PCA()" can be used to assess the stability and reproducibility of the dataset.

Usage

QC_PCA (metabo_SE, scale = FALSE, center = TRUE,...)

Arguments

metabo_SE	SummarizedExperiment object. See "MWAS_SummarizedExperiment()".
scale	logical constant indicating whether the metabolic variables will be scaled to have unit variance before the analysis. For more details, check "prcomp()".
center	logical constant indicating whether the metabolic variables will be shifted to be zero-centered before the analysis. For more details, check "prcomp()".
...	other arguments passed to "prcomp()".

Value

A list with class "prcomp". For more details, check "prcomp()".

References

Mardia K, et al. (1979). Multivariate Analysis, London: Academic Press.

Examples

## Load data
data(metabo_SE)
data(targetMetabo_SE)


## PCA model using all metabolic data
PCA_model <- QC_PCA (metabo_SE)

## PCA model using target metabolites
PCA_subset <- QC_PCA (targetMetabo_SE)

MWASTools documentation built on Nov. 8, 2020, 5:07 p.m.