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Applied Microbiome Statistics : Correlation, Association, Interaction and Composition

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Τίτλος: Applied Microbiome Statistics : Correlation, Association, Interaction and Composition
Περιγραφή: 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.
Συγγραφείς: Yinglin Xia, Jun Sun
Resource Type: eBook.
Θέματα: Microbiomes--Statistics, Microbiomes--Statistical methods, Microbial ecology--Statistical methods
Categories: SCIENCE / Life Sciences / Microbiology, MATHEMATICS / Probability & Statistics / General
Βάση Δεδομένων: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 3772426
RelevancyScore: 981
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 981.043701171875
IllustrationInfo
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  Data: Applied Microbiome Statistics : Correlation, Association, Interaction and Composition
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  Data: 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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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 579.0727
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Microbiomes--Statistics
        Type: general
      – SubjectFull: Microbiomes--Statistical methods
        Type: general
      – SubjectFull: Microbial ecology--Statistical methods
        Type: general
    Titles:
      – TitleFull: Applied Microbiome Statistics : Correlation, Association, Interaction and Composition
        Type: main
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            NameFull: Yinglin Xia
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            NameFull: Jun Sun
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            NameFull: Yinglin Xia
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            NameFull: Jun Sun
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
            – D: 27
              M: 08
              Type: profile
              Y: 2024
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            – Type: isbn-print
              Value: 9780367639709
            – Type: isbn-print
              Value: 9780367639716
            – Type: isbn-electronic
              Value: 9781003121572
            – Type: isbn-electronic
              Value: 9781040045664
            – Type: isbn-electronic
              Value: 9781040045701
          Titles:
            – TitleFull: Applied Microbiome Statistics : Correlation, Association, Interaction and Composition
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