Omics_PLSDA: Principal component analysis (PCA) analysis on Omics data...

In MASHUOA/MassOmics: Data extraction pipeline for large-scale GC-MS metabolomics datasets

Principal component analysis (PCA) analysis on Omics data sets

Description

Principal component analysis (PCA) is used to compress the dimension of multivariate data, and thereby display outliers and relationships between samples or classification of conditions. Under <Statistics> click <Run PCA> and a user interface window will appear to adjust a number of conditions, sphere radius, text size, log transfor-mation, and model validations. To plot 3 dimensional PCA, click <submit> and a pop-out window will allow the user to classify sam-ples into each group. All parameters can be changed on the user inter-face of PCA and replotted instantly via the <Re-Plot> function.

Usage

Omics_PLSDA()

Value

None

Examples

Omics_PLSDA()

MASHUOA/MassOmics documentation built on Nov. 3, 2023, 10:48 p.m.