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

Description Usage Value Examples

View source: R/statistics.R

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

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Examples

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MASHUOA/MassOmics documentation built on Jan. 23, 2022, 9:08 p.m.