Statistical and Computational Methods for Microbiome Multi-Omics Data
Title | Statistical and Computational Methods for Microbiome Multi-Omics Data PDF eBook |
Author | Himel Mallick |
Publisher | Frontiers Media SA |
Total Pages | 170 |
Release | 2020-11-19 |
Genre | Science |
ISBN | 2889660915 |
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Computational Methods for Microbiome Analysis
Title | Computational Methods for Microbiome Analysis PDF eBook |
Author | Joao Carlos Setubal |
Publisher | Frontiers Media SA |
Total Pages | 170 |
Release | 2021-02-02 |
Genre | Science |
ISBN | 2889664376 |
Handbook of Statistical Genomics
Title | Handbook of Statistical Genomics PDF eBook |
Author | David J. Balding |
Publisher | John Wiley & Sons |
Total Pages | 1828 |
Release | 2019-07-09 |
Genre | Science |
ISBN | 1119429250 |
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Computational methods for microbiome analysis, volume 2
Title | Computational methods for microbiome analysis, volume 2 PDF eBook |
Author | Setubal |
Publisher | Frontiers Media SA |
Total Pages | 223 |
Release | 2023-01-04 |
Genre | Science |
ISBN | 2832506402 |
Statistical Analysis of Microbiome Data
Title | Statistical Analysis of Microbiome Data PDF eBook |
Author | Somnath Datta |
Publisher | Springer Nature |
Total Pages | 349 |
Release | 2021-10-27 |
Genre | Medical |
ISBN | 3030733513 |
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.
Methods for Single-Cell and Microbiome Sequencing Data
Title | Methods for Single-Cell and Microbiome Sequencing Data PDF eBook |
Author | Himel Mallick |
Publisher | Frontiers Media SA |
Total Pages | 129 |
Release | 2022-05-31 |
Genre | Science |
ISBN | 2889762807 |
Statistical Data Analysis of Microbiomes and Metabolomics
Title | Statistical Data Analysis of Microbiomes and Metabolomics PDF eBook |
Author | Yinglin Xia |
Publisher | American Chemical Society |
Total Pages | 229 |
Release | 2022-02-03 |
Genre | Science |
ISBN | 0841299161 |
Compared with other research fields, both microbiome and metabolomics data are complicated and have some unique characteristics, respectively. Thus, choosing an appropriate statistical test or method is a very important step in the analysis of microbiome and metabolomics data. However, this is still a difficult task for those biomedical researchers without a statistical background and for those biostatisticians who do not have research experiences in these fields. Graduate students studying microbiome and metabolomics; statisticians, working on microbiome and metabolomics projects, either for their own research, or for their collaborative research for experimental design, grant application, and data analysis; and researchers who investigate biomedical and biochemical projects with the microbiome, metabolome, and multi-omics data analysis will benefit from reading this work.