Applied Microbiome Statistics

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Applied Microbiome Statistics

Applied Microbiome Statistics
Author :
Publisher : CRC Press
Total Pages : 457
Release :
ISBN-10 : 9781040045664
ISBN-13 : 1040045669
Rating : 4/5 (669 Downloads)

Book Synopsis Applied Microbiome Statistics by : Yinglin Xia

Download or read book Applied Microbiome Statistics written by Yinglin Xia and published by CRC Press. This book was released on 2024-07-22 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book officially defines microbiome statistics as a specific new field of statistics and addresses the statistical analysis of correlation, association, interaction, and composition in microbiome research. It also defines the study of the microbiome as a hypothesis-driven experimental science and describes two microbiome research themes and six unique characteristics of microbiome data, as well as investigating challenges for statistical analysis of microbiome data using the standard statistical methods. This book is useful for researchers of biostatistics, ecology, and data analysts. Presents a thorough overview of statistical methods in microbiome statistics of parametric and nonparametric correlation, association, interaction, and composition adopted from classical statistics and ecology and specifically designed for microbiome research. Performs step-by-step statistical analysis of correlation, association, interaction, and composition in microbiome data. Discusses the issues of statistical analysis of microbiome data: high dimensionality, compositionality, sparsity, overdispersion, zero-inflation, and heterogeneity. Investigates statistical methods on multiple comparisons and multiple hypothesis testing and applications to microbiome data. Introduces a series of exploratory tools to visualize composition and correlation of microbial taxa by barplot, heatmap, and correlation plot. Employs the Kruskal–Wallis rank-sum test to perform model selection for further multi-omics data integration. Offers R code and the datasets from the authors’ real microbiome research and publicly available data for the analysis used. Remarks on the advantages and disadvantages of each of the methods used.


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