Statistical Analysis of Microbiome Data with R [electronic resource] / by Yinglin Xia, Jun Sun, Ding-Geng Chen.

By: Xia, Yinglin [author.]Contributor(s): Sun, Jun | Chen, Ding-GengMaterial type: TextTextSeries: ICSA Book Series in StatisticsPublisher: Singapore : Springer Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018Description: XXIII, 505 p. 84 illus., 67 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9789811315343Subject(s): Statistics  | Big data | Statistics and Computing/Statistics Programs | Statistics for Life Sciences, Medicine, Health Sciences | Big DataDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
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.
Summary: 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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
e-Books e-Books Central Library, Sikkim University
519.5 (Browse shelf(Opens below)) Not for loan E-3118
Total holds: 0

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.

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.

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