Statistical Analysis of Microbiome Data with R

• Main Authors: Xia, Yinglin (Author, http://id.loc.gov/vocabulary/relators/aut), Sun, Jun (http://id.loc.gov/vocabulary/relators/aut), Chen, Ding-Geng (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: ICSA Book Series in Statistics,
• Subjects: Statistics .; Big data.; Statistics and Computing/Statistics Programs.; Statistics for Life Sciences, Medicine, Health Sciences.; Big Data.

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 pr...

Table of Contents:

• Chapter 1: Introduction to R, RStudio and ggplot2
• Chapter 2: What are Microbiome Data?
• Chapter 3: Bioinformatic and Statistical Analyses of Microbiome Data
• Chapter 4: Power and Sample Size Calculation in Hypothesis Testing Microbiome Data
• Chapter 5: Microbiome Data Management
• Chapter 6: Exploratory Analysis of Microbiome Data
• Chapter 7: Comparisons of Diversities, OTUs and Taxa among Groups
• Chapter 8: Community Composition Study
• Chapter 9: Modeling Over-dispersed Microbiome Data
• Chapter 10: Linear Regression Modeling metadata
• Chapter 11: Modeling Zero-Inflated Microbiome Data.