Multivariate Data Integration Using R

"This book was eagerly awaited both to bring together numerous research works published in recent years and to support the use of the Mixomics software which has become an essential tool for data integration and exploration when dealing with multiple types of high-dimensional biological data. It is the result of many years of research on cutting-edge developments in this domain as for sparsity. The book is very pleasant to read and well-structured around the different multivariate approaches. It is well documented with many recent references on the statistical methods and is very didactic through numerous examples accompanied by R codes and illustrations. It can be used by a large audience of statisticians and biologists to process, analyze, visualize, and interpret their multivariate microbiome and multi-omics data, but also as a basis for a course. I highly recommend this book."
- Philippe Bastien, Senior Research Associate - L'Oreal R&I

"The book belongs to the Computational Biology Series and presents a wide spectrum of modern methods of multivariate statistical analysis, integration and high-dimension reduction for biological data evaluated via the specialized R package. The neologism Omic is used as a root related to constellations of objects with biological information, for instance, in genomes and proteins-genomics and proteomics (in studying proteins expressed by cells and tissues), metabolic and transcription products-metabolomics and transcriptomics (in studying messenger RNA molecules expressed from the gens of an organism), or also in economics-Reaganomics, etc.

[. . . ] Numerous links to the internet websites related to the considered methods of multi-omics data integration are suggested, particularly, the mixOmics project is described at the link http://www.mixOmics.org, and the package is available at Install |mixOmics. The developed methods and software are suitable not only for biologists and bioinformaticians students and researchers, but can be useful for solving computational and content problems in many other fields as well."
- Technometrics

"This is an excellent book for computational biologists, bioinformaticians, statisticians, data scientists, and graduate students who work with high-throughput omics data. The book covers most fundamental concepts of multi-omics data integration, while focusing on their implementations through hands-on examples implemented in the mixOmics R package."
- Yuehua Cui, Michigan State University, Biometrics, September 2022