Download or read book Statistical Analysis of Microbiome Data with R written by Yinglin Xia and published by Springer. This book was released on 2018-10-06 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applied Microbiome Statistics written by Yinglin Xia and published by CRC Press. This book was released on 2024-07-22 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Analysis of Microbiome Data written by Somnath Datta and published by Springer Nature. This book was released on 2021-10-27 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Data Analysis of Microbiomes and Metabolomics written by Yinglin Xia and published by American Chemical Society. This book was released on 2022-02-03 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bioinformatic and Statistical Analysis of Microbiome Data written by Yinglin Xia and published by Springer Nature. This book was released on 2023-06-16 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 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. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.
Download or read book The Human Microbiome Diet and Health written by Food Forum and published by National Academies Press. This book was released on 2013-02-27 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Food Forum convened a public workshop on February 22-23, 2012, to explore current and emerging knowledge of the human microbiome, its role in human health, its interaction with the diet, and the translation of new research findings into tools and products that improve the nutritional quality of the food supply. The Human Microbiome, Diet, and Health: Workshop Summary summarizes the presentations and discussions that took place during the workshop. Over the two day workshop, several themes covered included: The microbiome is integral to human physiology, health, and disease. The microbiome is arguably the most intimate connection that humans have with their external environment, mostly through diet. Given the emerging nature of research on the microbiome, some important methodology issues might still have to be resolved with respect to undersampling and a lack of causal and mechanistic studies. Dietary interventions intended to have an impact on host biology via their impact on the microbiome are being developed, and the market for these products is seeing tremendous success. However, the current regulatory framework poses challenges to industry interest and investment.
Download or read book Statistical and Computational Methods for Microbiome Multi Omics Data written by Himel Mallick and published by Frontiers Media SA. This book was released on 2020-11-19 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Environmental Chemicals the Human Microbiome and Health Risk written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-03-01 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: A great number of diverse microorganisms inhabit the human body and are collectively referred to as the human microbiome. Until recently, the role of the human microbiome in maintaining human health was not fully appreciated. Today, however, research is beginning to elucidate associations between perturbations in the human microbiome and human disease and the factors that might be responsible for the perturbations. Studies have indicated that the human microbiome could be affected by environmental chemicals or could modulate exposure to environmental chemicals. Environmental Chemicals, the Human Microbiome, and Health Risk presents a research strategy to improve our understanding of the interactions between environmental chemicals and the human microbiome and the implications of those interactions for human health risk. This report identifies barriers to such research and opportunities for collaboration, highlights key aspects of the human microbiome and its relation to health, describes potential interactions between environmental chemicals and the human microbiome, reviews the risk-assessment framework and reasons for incorporating chemicalâ€"microbiome interactions.
Download or read book Microbiome Analysis written by Robert G. Beiko and published by . This book was released on 2018 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Chemistry of Microbiomes written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-07-19 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 21st century has witnessed a complete revolution in the understanding and description of bacteria in eco- systems and microbial assemblages, and how they are regulated by complex interactions among microbes, hosts, and environments. The human organism is no longer considered a monolithic assembly of tissues, but is instead a true ecosystem composed of human cells, bacteria, fungi, algae, and viruses. As such, humans are not unlike other complex ecosystems containing microbial assemblages observed in the marine and earth environments. They all share a basic functional principle: Chemical communication is the universal language that allows such groups to properly function together. These chemical networks regulate interactions like metabolic exchange, antibiosis and symbiosis, and communication. The National Academies of Sciences, Engineering, and Medicine's Chemical Sciences Roundtable organized a series of four seminars in the autumn of 2016 to explore the current advances, opportunities, and challenges toward unveiling this "chemical dark matter" and its role in the regulation and function of different ecosystems. The first three focused on specific ecosystemsâ€"earth, marine, and humanâ€"and the last on all microbiome systems. This publication summarizes the presentations and discussions from the seminars.
Download or read book Statistical Issues in Microbiome Data Analysis written by Weijia Fu and published by . This book was released on 2019 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Human Microbiome written by Mohsin Khurshid and published by Springer Nature. This book was released on with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Integrated Analysis of Microbiomes and Metabolomics written by Yinglin Xia and published by American Chemical Society. This book was released on 2022-03-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Novel Approaches in Microbiome Analyses and Data Visualization written by Jessica Galloway-Peña and published by Frontiers Media SA. This book was released on 2019-02-06 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Microbiomes of the Built Environment written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-10-06 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: People's desire to understand the environments in which they live is a natural one. People spend most of their time in spaces and structures designed, built, and managed by humans, and it is estimated that people in developed countries now spend 90 percent of their lives indoors. As people move from homes to workplaces, traveling in cars and on transit systems, microorganisms are continually with and around them. The human-associated microbes that are shed, along with the human behaviors that affect their transport and removal, make significant contributions to the diversity of the indoor microbiome. The characteristics of "healthy" indoor environments cannot yet be defined, nor do microbial, clinical, and building researchers yet understand how to modify features of indoor environmentsâ€"such as building ventilation systems and the chemistry of building materialsâ€"in ways that would have predictable impacts on microbial communities to promote health and prevent disease. The factors that affect the environments within buildings, the ways in which building characteristics influence the composition and function of indoor microbial communities, and the ways in which these microbial communities relate to human health and well-being are extraordinarily complex and can be explored only as a dynamic, interconnected ecosystem by engaging the fields of microbial biology and ecology, chemistry, building science, and human physiology. This report reviews what is known about the intersection of these disciplines, and how new tools may facilitate advances in understanding the ecosystem of built environments, indoor microbiomes, and effects on human health and well-being. It offers a research agenda to generate the information needed so that stakeholders with an interest in understanding the impacts of built environments will be able to make more informed decisions.
Download or read book Statistical Methods for the Analysis of Microbiome Data written by Anna M. Plantinga and published by . This book was released on 2018 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: The human microbiome plays a vital role in maintaining health, and imbalances in the microbiome are associated with a wide variety of diseases. Understanding whether and how the microbiome is associated with particular health conditions is a focus of many modern microbiome studies, with the hope that a deeper understanding of these associations may lead to more effective prevention and treatment regimens. However, how best to analyze data from microbiome profiling studies remains unclear. The high dimensionality, compositional nature, intrinsic biological structure, and limited availability of samples pose substantial statistical challenges. To face these challenges, we propose novel analytic approaches based on sparse penalized regression strategies and distance-based global association analysis. Most distance-based methods for global microbiome association analysis are restricted to simple dichotomous or quantitative outcomes, but more complex outcomes are increasingly common in microbiome studies. In the first part of this dissertation, we introduce two distance-based methods for the analysis of entire microbial communities in modern microbiome studies. We develop a kernel machine regression-based score test for association between the microbiome and censored time-to-event outcomes. We then propose a novel longitudinal measure of dissimilarity that summarizes changes in the microbiome across time and compares these changes between subjects. Since this dissimilarity may be incorporated into any distance-based analysis framework, it is a highly flexible tool for applying a wide variety of distance-based analyses in longitudinal studies. Identification of associated taxa and detection of predictive microbial signatures are key to translation of microbiome studies. In the second part of this dissertation, we present two penalized regression methods for estimation and prediction with high-dimensional compositional data. Because phylogenetic similarity between bacteria often corresponds to shared functions, our first contribution is to incorporate phylogenetic structure into a penalized regression model for constrained data. We then propose a model that exploits phylogenetic structure to use partial information in the setting of differing feature sets between model-building and prediction datasets. We evaluate the performance of these methods through extensive simulation studies and apply them to studies investigating the association of graft-versus-host disease or body mass index with the gut microbiome.
Download or read book Topics in Applied Statistics written by Mingxiu Hu and published by Springer Science & Business Media. This book was released on 2013-09-14 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents 27 selected papers in topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. All papers feature original, peer-reviewed content. The editors intentionally selected papers that cover many topics so that the volume will serve the whole statistical community and a variety of research interests. The papers represent select contributions to the 21st ICSA Applied Statistics Symposium. The International Chinese Statistical Association (ICSA) Symposium took place between the 23rd and 26th of June, 2012 in Boston, Massachusetts. It was co-sponsored by the International Society for Biopharmaceutical Statistics (ISBS) and American Statistical Association (ASA). This is the inaugural proceedings volume to share research from the ICSA Applied Statistics Symposium.
