Bioinformatic and Statistical Analysis of Microbiome Data: From Raw Sequences to Advanced Modeling with QIIME 2 and R
β Scribed by Yinglin Xia, Jun Sun
- Publisher
- Springer
- Year
- 2023
- Tongue
- English
- Leaves
- 729
- Edition
- 1st ed. 2023
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow forΒ microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. Β It includes real-world data from the authorsβ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 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.
Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.
π SIMILAR VOLUMES
<p><span>This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow forΒ microbiome data analysis:
This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authorsβ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer program
<p><P>Not only is the quantity of life science data expanding, but new types of biological data continue to be introduced as a result of technological development and a growing understanding of biological systems. Methods for analyzing these data are an increasingly important component of modern bio