rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Statistical Analysis of Microbiome Data
  name:
    name part: Datta, Somnath.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Guha, Subharup.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2021
    edition: 1st ed. 2021.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XIV, 346 pages 64 illustrations, 49 illustrations in color.)
  abstract: Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
  table of contents: 1. Tree-guided regression and multivariate analysis of microbiome data - Hongu Zhao and Tao Wang -- 2. Computational methods for metagenomic assemblies and strain identification - Hongzhe Li -- 3. Graphical models for microbiome data - Ali Shojaie -- 4. Bayesian models for understanding the modulating factors of microbiome data - Francesco Denti, Matthew D. Koslovsky, Michele Guindani, Marina Vannucci, and Katrine L. Whiteson -- 5. Use of variable importance in microbiome studies - Hemant Ishwaran -- 6. Log-linear models for microbiome data - Glen Satten -- 7. Quantification of amplicon sequences in microbiome samples using statistical methods - Karin Dorman -- 8. TBD - Jeanine Houwing Duistermaat -- 9. Analyzing microbiome data by employing the power of abundance ratios - Zhigang Li -- 10. Beta diversity analysis - Michael Wu -- 11. MicroPro: using metagenomic unmapped reads to provide insights into human microbiota and disease associations - Fengzhu Sun -- 12. Statistical methods for feature selection in microbiome studies - Peng Liu -- 13. A Bayesian restoration of the duality between principal components of a distance matrix and operational taxonomic units in microbiome analyses - Somnath Datta and Subharup Guha.
  note: edited by Somnath Datta, Subharup Guha.
  subject:
    topic: Statistics
  subject:
    topic: Biostatistics
  subject:
    topic: Genetics
  subject:
    topic: Big data
  subject:
    topic: Microbiology
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  subject:
    topic: Biostatistics
  subject:
    topic: Genetics and Genomics
  subject:
    topic: Big Data
  subject:
    topic: Microbiology
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Frontiers in Probability and the Statistical Sciences
  identifier: 9783030733513
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 211027
    record change date: 20230330185252.9
    record identifier: in00004378617