Book: Multivariate Data Integration Using R: Methods and Applications with the mixOmics package

We are excited to announce that our book is out, along with several case studies and R scripts available online. Check out this page. It’s been a very (very) long term project, and a great collaboration with Zoe Welham whose dedication and patience helped shape this project into a readable whole! A huge thank you to Al Abadi, who tirelessly helped updating the package as we developed the content.

 

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

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