Multivariate Data Integration Using R
eBook - ePub

Multivariate Data Integration Using R

Methods and Applications with the mixOmics Package

  1. 298 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Multivariate Data Integration Using R

Methods and Applications with the mixOmics Package

About this book

Large biological data, which are often noisy and high-dimensional, have become increasingly prevalent in biology and medicine. There is a real need for good training in statistics, from data exploration through to analysis and interpretation. This book provides an overview of statistical and dimension reduction methods for high-throughput biological data, with a specific focus on data integration. It starts with some biological background, key concepts underlying the multivariate methods, and then covers an array of methods implemented using the mixOmics package in R.

Features:

  • Provides a broad and accessible overview of methods for multi-omics data integration
  • Covers a wide range of multivariate methods, each designed to answer specific biological questions
  • Includes comprehensive visualisation techniques to aid in data interpretation
  • Includes many worked examples and case studies using real data
  • Includes reproducible R code for each multivariate method, using the mixOmics package

The book is suitable for researchers from a wide range of scientific disciplines wishing to apply these methods to obtain new and deeper insights into biological mechanisms and biomedical problems. The suite of tools introduced in this book will enable students and scientists to work at the interface between, and provide critical collaborative expertise to, biologists, bioinformaticians, statisticians and clinicians.

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Yes, you can access Multivariate Data Integration Using R by Kim-Anh LeCao,Zoe Marie Welham,Kim-Anh Lê Cao in PDF and/or ePUB format, as well as other popular books in Mathematics & Biology. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Contents
  8. Preface
  9. Authors
  10. I Modern biology and multivariate analysis
  11. II mixOmics under the hood
  12. III mixOmics in action
  13. Glossary of terms
  14. Key publications
  15. Bibliography
  16. Index