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Statistical Analysis of Microbiome Data with R

Statistical Analysis of Microbiome Data with R PDF Author: Yinglin Xia
Publisher: Springer
ISBN: 9811315345
Category : Computers
Languages : en
Pages : 505

Book Description
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.

Statistical Analysis of Microbiome Data with R

Statistical Analysis of Microbiome Data with R PDF Author: Yinglin Xia
Publisher: Springer
ISBN: 9811315345
Category : Computers
Languages : en
Pages : 505
Book Description
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.

Statistical Analysis of Microbiome Data

Statistical Analysis of Microbiome Data PDF Author: Somnath Datta
Publisher: Springer Nature
ISBN: 3030733513
Category : Big data
Languages : en
Pages : 346
Book Description
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.

Statistical Data Analysis of Microbiomes and Metabolomics

Statistical Data Analysis of Microbiomes and Metabolomics PDF Author: Yinglin Xia
Publisher: American Chemical Society
ISBN: 0841299161
Category : Science
Languages : en
Pages : 100
Book Description
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. Statistical Data Analysis of Microbiomes and Metabolomics focuses on data analysis, statistical methods, and models. The general goal of this primer is to provide our readers with: (1) The challenges of analyzing microbiome and metabolomics data using the standard models and methods. (2) The new specifically designed methods and models developed to target the unique characteristics of microbiome data. (3) The strengths and weaknesses of the newly developed methods and models. (4) A comparison of the same categories of methods, based on their nature and capabilities, including whether the methods fit different types of data. (5) Explanations for whether the tested methods and used models with their assumptions and attributes are amenable to the tested data. (6) References to real studies to illustrate each of the important methods and models. 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.

An Integrated Analysis of Microbiomes and Metabolomics

An Integrated Analysis of Microbiomes and Metabolomics PDF Author: Yinglin Xia
Publisher: American Chemical Society
ISBN: 0841299544
Category : Science
Languages : en
Pages : 100
Book Description
Because the microbial community is dynamic, an individual’s microbiota at a given time is varied, and many factors, including age, host genetics, diet, and the local environment, significantly change the microbiota. Thus, microbiome researchers have naturally expanded their research to look for insights into the interaction of the microbiome with other “omics”. Metabolites (small molecules) are the intermediate or end products of metabolism. Metabolites have various functions. The microbial-derived metabolites play an important role in the function of the microbiome. Thus, the advancement in microbiome studies is becoming particularly critical for the integration of microbial DNA sequencing data with other omics data, especially microbiome-metabolomics integration.

Inflammation, Infection, and Microbiome in Cancers

Inflammation, Infection, and Microbiome in Cancers PDF Author: Jun Sun
Publisher: Springer Nature
ISBN: 3030679519
Category : Medical
Languages : en
Pages : 509
Book Description
This book offers a summary and discussion of the advances of inflammation and infection in various cancers. The authors cover the classically known virus infections in cancer, novel roles of other pathogens (e.g. bacteria and fungi), as well as biomarkers for diagnosis and therapy. Further, the chapters highlight the progress of immune therapy, stem cells and the role of the microbiome in the pathophysiology of cancers. Readers will gain insights into complex microbial communities, that inhabit most external human surfaces and play a key role in health and disease. Perturbations of host-microbe interactions often lead to altered host responses that can promote cancer development. Thus, this book highlights emerging roles of the microbiome in pathogenesis of cancers and outcome of therapy. The focus is on mechanistic concepts that underlie the complex relationships between host and microbes. Approaches that can inhibit infection, suppress chronic inflammation and reverse the dysbiosis are discussed, as a means for restoring the balance between host and microbes. This comprehensive work will be beneficial to researchers and students interested in infectious diseases, microbiome, and cancer as well as clinicians and general physiologists.

The Microbiome in Health and Disease

The Microbiome in Health and Disease PDF Author:
Publisher: Academic Press
ISBN: 0128200014
Category : Science
Languages : en
Pages : 520
Book Description
The Microbiome in Health and Disease, Volume 171 in the Progress in Molecular Biology and Translational Science series, provides the most topical, informative and exciting monographs available on a wide variety of research topics. The series includes in-depth knowledge on the molecular biological aspects of organismal physiology, with this release including chapters on Microbiome in health and disease, CNS development and microbiome in infants, A gut feeling in ALS, Microbiome (Virome) and virus infection, Bugs and Drugs: microbiome in medicine metabolism, Immunity, T cells, and microbiome, Salmonella (Bacterial) infection and cancer: of mice and men, and many other highly researched topics. Provides a novel theme and multiple disciplinary topics of microbiome research in basic and translational studies Presents an updated collection on bacteria, virus, fungi and their interactions in microbiome Includes a timely discussion on the tools and methods used for modeling and analysis of microbiome data

Mechanisms Underlying Host-Microbiome Interactions in Pathophysiology of Human Diseases

Mechanisms Underlying Host-Microbiome Interactions in Pathophysiology of Human Diseases PDF Author: Jun Sun
Publisher: Springer
ISBN: 149397534X
Category : Medical
Languages : en
Pages : 381
Book Description
Only recently have we begun to appreciate the role of microbiome in health and disease. Environmental factors and change of life style including diet significantly shape human microbiome that in turn appears to modify gut barrier function affecting nutrient & electrolyte absorption and inflammation. Approaches that can reverse the gut dysbiosis represent as reasonable and novel strategies for restoring the balance between host and microbes. In the book, we offer summary and discussion on the advances in understanding of pathophysiological mechanisms of microbial host interactions in human diseases. We will not only discuss intestinal bacterial community, but also viruses, fungi and oral microbiome. Microbiome studies will facilitate diagnosis, functional studies, drug development and personalized medicine. Thus, this book will further highlight the microbiome in the context of health and disease, focusing on mechanistic concepts that underlie the complex relationships between host and microbes.

Intestinal Dysbiosis in Inflammatory Diseases

Intestinal Dysbiosis in Inflammatory Diseases PDF Author: Gislane Lelis Vilela de Oliveira
Publisher: Frontiers Media SA
ISBN: 2889714055
Category : Medical
Languages : en
Pages :
Book Description
Dr. Fasano holds stocks in Alba Therapeutics and receives financial support from Takeda Pharmaceuticals. Dr. Taneja receives financial support from Elysium Health and Evelo Biosciences. The other Topic Editors declare no competing interests with regards to the Research Topic subject.

Novel Approaches in Microbiome Analyses and Data Visualization

Novel Approaches in Microbiome Analyses and Data Visualization PDF Author: Jessica Galloway-Peña
Publisher: Frontiers Media SA
ISBN: 2889456536
Category :
Languages : en
Pages :
Book Description
High-throughput sequencing technologies are widely used to study microbial ecology across species and habitats in order to understand the impacts of microbial communities on host health, metabolism, and the environment. Due to the dynamic nature of microbial communities, longitudinal microbiome analyses play an essential role in these types of investigations. Key questions in microbiome studies aim at identifying specific microbial taxa, enterotypes, genes, or metabolites associated with specific outcomes, as well as potential factors that influence microbial communities. However, the characteristics of microbiome data, such as sparsity and skewedness, combined with the nature of data collection, reflected often as uneven sampling or missing data, make commonly employed statistical approaches to handle repeated measures in longitudinal studies inadequate. Therefore, many researchers have begun to investigate methods that could improve incorporating these features when studying clinical, host, metabolic, or environmental associations with longitudinal microbiome data. In addition to the inferential aspect, it is also becoming apparent that visualization of high dimensional data in a way which is both intelligible and comprehensive is another difficult challenge that microbiome researchers face. Visualization is crucial in both the analysis and understanding of metagenomic data. Researchers must create clear graphic representations that give biological insight without being overly complicated. Thus, this Research Topic seeks to both review and provide novels approaches that are being developed to integrate microbiome data and complex metadata into meaningful mathematical, statistical and computational models. We believe this topic is fundamental to understanding the importance of microbial communities and provides a useful reference for other investigators approaching the field.

Statistical Issues in Microbiome Data Analysis

Statistical Issues in Microbiome Data Analysis PDF Author: Weijia Fu
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
Book Description
Progress in high throughput sequencing has facilitated the conduct of large scale microbiome profiling studies which have already begun to elucidate the role of microbes in many disorders and clinical outcomes. Despite the many successes, statistical analysis of data from these studies continues to pose a challenge. In the thesis, we proposed methods to study two specific challenges: batch effects and integrative analysis of microbiome and other omics data. Both issues are increasingly relevant problems. As studies get larger, batching becomes inevitable and integrative analysis is imperative for gaining clues as to the mechanisms underlying discovered associations. The thesis is composed of two projects. In the first project, we compared six existing batch correction methods for microarray data when applied to microbiome data. Two real microbiome data sets were used to evaluate the performance using data visualization and several evaluation metrics. Our results suggest that an empirical bayes approach (ComBat), when applied appropriately, can outperform other methods. In the second project, we proposed a robust microbiome regression-based kernel association test (MiRKAT-R) to screen a large number of genomic markers for association with microbiome profiles. This approach utilizes a recently developed robust kernel machine test. We further propose to incorporate an omnibus test that simultaneously considers different models so as to allow for different relationships between the individual markers and microbiome composition. Systematic simulations and applications to real data show that the MiRKAT-R improves both type I error control and power.