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 Statistical Methods for Longitudinal Data Analysis and Reproducible Feature Selection in Human Microbiome Studies written by Lingjing Jiang and published by . This book was released on 2020 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: The microbiome is inherently dynamic, driven by interactions among microbes, with the host, and with the environment. At any point in life, human microbiome can be dramatically altered, either transiently or long term, by diseases, medical interventions or even daily routines. Since the human microbiome is highly dynamic and personalized, longitudinal microbiome studies that sample human-associated microbial communities repeatedly over time provide valuable information for researchers to observe both inter- and intra-individual variability, or to measure changes in response to an intervention in real time. Despite this increasing need in longitudinal data analysis, statistical methods for analyzing sparse longitudinal microbiome data and longitudinal multi-omics data still lag behind. In this dissertation, we describe our efforts in developing two novel statistical methods, Bayesian functional principal components analysis (SFPCA) for sparse longitudinal data analysis, and multivariate sparse functional principal components analysis (mSFPCA) for longitudinal microbiome multi-omics data analysis. Beyond longitudinal data analysis, we are also interested in utilizing statistical techniques for addressing the "reproducibility crisis" in microbiome research, especially in the indispensable task of feature selection. Instead of developing "the best" feature selection method, we focus on discovering a reproducible criterion called Stability for evaluating feature selection methods in order to yield reproducible results in microbiome analysis. To set an appropriate motivation and context for our work, Chapter 1 reviews the importance of longitudinal studies in human microbiome research, and presents the crucial need of developing novel statistical methods to meet the new challenges in longitudinal microbiome data analysis, and of producing reproducible results in microbiome feature selection. Chapter 2 introduces Bayesian SFPCA, a flexible Bayesian approach to SFPCA that enables efficient model selection and graphical model diagnostics for valid longitudinal microbiome applications. Chapter 3 presents mSFPCA, an extension of Bayesian SFPCA from modeling a univariate temporal outcome to simultaneously characterizing multiple temporal measurements, and inferring their temporal associations based on mutual information estimation. Chapter 4 proposes to use reproducibility criterion such as Stability instead of popular model prediction metric such as mean squared error (MSE) to quantify the reproducibility of identified microbial features.
Download or read book Computational methods for microbiome analysis volume 2 written by Setubal and published by Frontiers Media SA. This book was released on 2023-01-04 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Biomedical Data Visualization Methods and Applications written by Guangchuang Yu and published by Frontiers Media SA. This book was released on 2022-05-24 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Visual and Functional Analysis of Microbiome Data written by Achal Dhariwal and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The advancements in next-generation sequencing technologies have revolutionized microbiome research by allowing culture-independent high-throughput profiling of the genetic contents of microbial communities. Nowadays, 16S rRNA based marker gene sequencing is widely used to characterize the taxonomic composition and phylogenetic diversity of complex microbial communities. However, statistical, visual and functional analysis of such data possess great challenges. In addition, many aspects of the current approaches can be improved to get a better understanding of communities. The proper analysis of the resulting large and complicated datasets remains a key bottleneck in current microbiome studies. Over the last decade, powerful computational pipelines and standard protocols have been developed to support efficient raw data processing and annotation of microbiome data. The focus has now shifted towards downstream statistical analysis and functional interpretation. To address this bottleneck, we have developed MicrobiomeAnalyst, a user-friendly web-based tool that incorporates recent progresses in statistics and interactive visualization techniques, coupled with novel knowledge bases, to facilitate comprehensive analysis of common data sets generated from microbiome studies. MicrobiomeAnalyst contains four major components, including i) a module for community diversity profiling, comparative analysis and functional prediction of 16S rRNA marker gene data; ii) a module for exploratory data analysis, functional profiling and metabolic network visualization for shotgun metagenomics or metatranscriptomics data; iii) a module to help users to interpret their taxa of interest via enrichment analysis against ~300 taxon sets manually collected from recent literature and public databases; and iv) a module to allow users to visually explore their data sets within the context of compatible public data (meta-analysis) for pattern discovery and biological insights. The tool is freely accessible at http://www.microbiomeanalyst.ca. " --
Download or read book Biocomputing 2017 Proceedings Of The Pacific Symposium written by Russ B Altman and published by World Scientific. This book was released on 2016-11-23 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB) 2017 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2017 will be held on January 4 - 8, 2017 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2017 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.
Download or read book Microbiome in Human Health and Disease written by Pallaval Veera Bramhachari and published by Springer Nature. This book was released on 2021-10-18 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an overview on how the microbiome contributes to human health and disease. The microbiome has also become a burgeoning field of research in medicine, agriculture & environment. The readers will obtain profound knowledge on the connection between intestinal microbiota and immune defense systems, medicine, agriculture & environment. The book may address several researchers, clinicians and scholars working in biomedicine, microbiology and immunology. The application of new technologies has no doubt revolutionized the research initiatives providing new insights into the dynamics of these complex microbial communities and their role in medicine, agriculture & environment shall be more emphasized. Drawing on broad range concepts of disciplines and model systems, this book primarily provides a conceptual framework for understanding these human-microbe, animal-microbe & plant-microbe, interactions while shedding critical light on the scientific challenges that lie ahead. Furthermore this book explains why microbiome research demands a creative and interdisciplinary thinking—the capacity to combine microbiology with human, animal and plant physiology, ecological theory with immunology, and evolutionary perspectives with metabolic science.This book provides an accessible and authoritative guide to the fundamental principles of microbiome science, an exciting and fast-emerging new discipline that is reshaping many aspects of the life sciences. These microbial partners can also drive ecologically important traits, from thermal tolerance to diet in a typical immune system, and have contributed to animal and plant diversification over long evolutionary timescales. Also this book explains why microbiome research presents a more complete picture of the biology of humans and other animals, and how it can deliver novel therapies for human health and new strategies.
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 505 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 Insights in Systems Microbiology 2021 written by George Tsiamis and published by Frontiers Media SA. This book was released on 2022-10-06 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Human Microbiota written by David N. Fredricks and published by John Wiley & Sons. This book was released on 2013-02-22 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Human Microbiota offers a comprehensive review of all human-associated microbial niches in a single volume, focusing on what modern tools in molecular microbiology are revealing about human microbiota, and how specific microbial communities can be associated with either beneficial effects or diseases. An excellent resource for microbiologists, physicians, infectious disease specialists, and others in the field, the book describes the latest research findings and evaluates the most innovative research approaches and technologies. Perspectives from pioneers in human microbial ecology are provided throughout.
Download or read book Computational Methods for Microbiome Analysis written by Joao Carlos Setubal and published by Frontiers Media SA. This book was released on 2021-02-02 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Microbiome and Machine Learning written by Isabel Moreno Indias and published by Frontiers Media SA. This book was released on 2022-08-02 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Novel Approaches for Analysis and Utilization of Human Gut Metaproteomics Data written by Mouses Stamboulian and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in sequencing technology enabled the recovery of genetic material sequenced directly from environmental samples through metagenomics. Metagenomics, based on high-throughput sequencing technologies, revolutionized microbial studies by extracting their genome directly from their natural communities and ecologies. This expanded the taxonomic and functional diversities of many microbial communities, which was not previously possible due to limitations of culture based sequencing techniques of the individual organisms. Among the many microbial populations within different environments, there has been a particular focus and emphasis towards the human gut microbiome due to the important role played by it in the well-being of their hosts. A growing number of literature reports the importance of the human gut microbiome in both human health and disease with most findings claiming its relation to dysbiosis in their composition and functionality. The dramatic increase in deeply sequenced metagenomic datasets, from different initiatives, such as the human microbiome project (HMP I&II), MetaHIT and the Integrated Gut Catalog (IGC), have shaped and furthered our understanding of the complex relationships among these microscopic entities as well as their hosts. By taking advantage of these efforts, in this dissertation (1) we inferred a large human gut microbial tree of life, by curating more than 6,000 gut microbial whole genome sequences covering to a great extent the diversity presented by this complex ecology. Next (2) we employed this microbial genome catalogue and developed a reference based peptide identification pipeline (called HAPiID), which provides a universal framework for metaproteomics based analysis of the human gut, and enables reproducible and comparable studies. Motivated by the increasing availability of metaproteomics datasets of human microbiome, (3) we conducted a large scale analysis of more than one thousand metaproteomics datasets to study microbial proteins and their expression in the microbiome of healthy individuals and individuals with different diseases, and assessed the capacity of various microbial features in predicting host phenotypes by employing machine learning techniques. Finally, based on a large scale survey of metaproteomic data of human gut microbiome, (4) we were able to characterize the protein expression landscape of a large number of human-associated microbial species, which otherwise would only be studied one at a time using culture based proteomics approach, enabling the identification of species that are ubiquitously expressed in the human population (generalists), and species that are highly expressed however only in a small subset of individuals associated with a certain phenotype (specialists).
Download or read book Benchmarking and Acceleration of Machine Learning and Analytics Pipelines for Large Microbiome Datasets written by George Wesley Armstrong and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the past decade, the number of publicly available microbiome sequencing samples has increased dramatically. Consequently, bottlenecks have arisen in common analysis steps, such as processing the sequencing data and characterizing the content of the microbial communities. Over this timespan, new tools have also been developed for steps such as alignment and dimensionality reduction that scale better or handle the additional complexity of high-dimensional data, however, their characteristics on microbiome data were previously uncharacterized. In this dissertation, we accelerate the analysis of microbiomes by introducing new methods or benchmarking alternatives. Additionally, we compare the results of novel methodology to existing best-practices on gold-standard datasets to determine whether the methods adequately address the specific challenges of microbiome data. In the first part of this work, Chapter 1 reviews many aspects of microbiome data that necessitate the use of microbiome-specific techniques for analyzing collections of microbial communities. Chapter 2 then introduces SFPhD, a novel approach for calculating phylogenetic alpha diversity that leverages the characteristics of microbiome data to speed up and reduce the memory requirements of a costly single-sample characterization. In the second part of the work, we apply recently developed tools for machine learning and sequencing pre-processing to demonstrate their potential for elucidating complex relationships in microbial data and reducing the lead time for supporting clinical applications of metagenomic sequencing, respectively. Chapter 3 demonstrates how Uniform Manifold Approximation and Projection (UMAP) provides succinct representations of data compared to the long-time standard method of microbial ecology, Principal Coordinates Analysis (PCoA). Importantly, UMAP provides different guarantees about the preservation of local/global geometry in its representation and careful consideration should be given to its application. In Chapter 4, we show that the popular metagenomic preprocessing pipeline of Atropos for adapter trimming and Bowtie2 for host filtering can be replaced by a substantially faster combination of Fastp and Minimap2, respectively. Furthermore, we have determined that the results this new pipeline produces are comparable to the outputs produced by the original pipeline.
Download or read book Microbial Omics in Environment and Health written by Minu Kesheri and published by Springer Nature. This book was released on with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt:
