Our book is out and is available in printed and electronic format. Case studies vignettes are available here (excluding the methodological aspects), and the R codefor each chapter / case study can be downloaded here.

Lê Cao K-A. and Welham Z. Multivariate Data Integration Using R: Methods and Applications with the mixOmics package. CRC Chapman & Hall.

Table of Contents

I Modern biology and multivariate analysis

1. Multi-omics and biological systems
2. The cycle of analysis
3. Key multivariate concepts and dimension reduction in mixOmics
4. Choose the right method for the right question in mixOmics

II mixOmics under the hood

5. Projection to Latent Structures
6. Visualisation for data integration
7. Performance assessment in multivariate analyses

III mixOmics in action

8. mixOmics: get started
9. Principal Component Analysis (PCA)
10. 10 Projection to Latent Structure (PLS)
11. Canonical Correlation Analysis (CCA)
12. PLS – Discriminant Analysis (PLS-DA)
13. N − data integration
14. P − data integration