Multivariate data integration using R : methods and applications with the mixOmics package /

Bibliographic Details
Main Authors:	LeÌ‚ Cao, Kim-Anh (Author), Welham, Zoe (Author)
Corporate Author:	ProQuest (Firm)
Format:	eBook
Language:	English
Published:	Boca Raton, FL : CRC Press, Taylor & Francis Group, 2022.
Edition:	First edition.
Series:	Computational biology.
Subjects:	Biometry. Multivariate analysis. R (Computer program language) COMPUTERS / Bioinformatics Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

I Modern biology and multivariate analysis 1. Multi-omics and biological systems 2. The cycle of analysi3. Key multivariate concepts and dimension reduction in mixOmics . Choose the right method for the right question in mixOmics ixOmics under the hood 5. Projection to Latent Structures . Visualisation for data integration . Performance assessment in multivariate analyses II mixOmics in action . mixOmics: get started . Principal Component Analysis (PCA) 10 Projection to Latent Structure (PLS) 1. Canonical Correlation Analysis (CCA) 2. PLS
Discriminant Analysis (PLS-DA) 3. N data integration 4. P data integration 5. (APPENDIX) Glossary of Terms