Statistical Analysis of Microbiome Data with R

Yinglin Xia

ISBN 10: 9811346453 / ISBN 13: 9789811346453

Edité par Springer Nature Singapore, Springer Nature Singapore, 2018

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors' research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.

N° de réf. du vendeur 9789811346453

Détails bibliographiques

• Titre: Statistical Analysis of Microbiome Data with R
• Éditeur: Springer Nature Singapore, Springer Nature Singapore
• Date de parution: 2018
• Langue: anglais
• ISBN à 10 chiffres: 9811346453
• ISBN à 13 chiffres: 9789811346453
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors' research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research.

The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.