[PDF] Omic Association Studies With R And Bioconductor eBook

Author : Juan R. González
Publisher : CRC Press
Page : 376 pages
File Size : 35,15 MB
Release : 2019-06-14
Category : Mathematics
ISBN : 0429803370

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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies. Newcomers to the field are confronted with a wealth of data, resources and methods. This book presents current methods to perform informative analyses using real and illustrative data with established bioinformatics tools and guides the reader through the use of publicly available data. Includes clear, readable programming codes for readers to reproduce and adapt to their own data. Emphasises extracting biologically meaningful associations between traits of interest and genomic, transcriptomic and epigenomic data Uses up-to-date methods to exploit omic data Presents methods through specific examples and computing sessions Supplemented by a website, including code, datasets, and solutions

Author : Juan R. González
Publisher : CRC Press
Page : 348 pages
File Size : 25,84 MB
Release : 2019-06-14
Category : Mathematics
ISBN : 0429803362

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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured in recent years, and they are a keystone in large epidemiological studies. Newcomers to the field are confronted with a wealth of data, resources and methods. This book presents current methods to perform informative analyses using real and illustrative data with established bioinformatics tools and guides the reader through the use of publicly available data. Includes clear, readable programming codes for readers to reproduce and adapt to their own data. Emphasises extracting biologically meaningful associations between traits of interest and genomic, transcriptomic and epigenomic data Uses up-to-date methods to exploit omic data Presents methods through specific examples and computing sessions Supplemented by a website, including code, datasets, and solutions

Author : Ebru Çağlayan Akay - Merve Ertok Onurlu
Publisher : HOLISTENCE PUBLICATIONS
Page : 419 pages
File Size : 43,64 MB
Release : 2023-03-21
Category : Language Arts & Disciplines
ISBN : 6256942140

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In the world, many women are at risk of being exposed to economic, physical, sexual, psychological, and emotional violence, or even intentional homicide. They might also be exposed to discrimination based on their socio-demographic characteristics, such as their ethnic background, religion, and educational level. The purpose of this book is to bring together academics and researchers working in the fields of applied econometrics and applied statistics as they pertain to women’s issues. The twelve-chapter book includes insights on present econometric and statistical methodologies on women’s issues, as well as a better understanding and evaluation of contemporary policy implications, initiatives, and procedures pertaining to women.

Author : Paolo Tieri
Publisher : Frontiers Media SA
Page : 137 pages
File Size : 32,30 MB
Release : 2015-09-17
Category : Science (General)
ISBN : 2889196488

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Stable, predictive biomarkers and interpretable disease signatures are seen as a significant step towards personalized medicine. In this perspective, integration of multi-omic data coming from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strategy to reconstruct and analyse complex multi-dimensional interactions, enabling deeper mechanistic and medical insight. At the same time, there is a rising concern that much of such different omic data –although often publicly and freely available- lie in databases and repositories underutilised or not used at all. Issues coming from lack of standardisation and shared biological identities are also well-known. From these considerations, a novel, pressing request arises from the life sciences to design methodologies and approaches that allow for these data to be interpreted as a whole, i.e. as intertwined molecular signatures containing genes, proteins, mRNAs and miRNAs, able to capture inter-layers connections and complexity. Papers discuss data integration approaches and methods of several types and extents, their application in understanding the pathogenesis of specific diseases or in identifying candidate biomarkers to exploit the full benefit of multi-omic datasets and their intrinsic information content. Topics of interest include, but are not limited to: • Methods for the integration of layered data, including, but not limited to, genomics, transcriptomics, glycomics, proteomics, metabolomics; • Application of multi-omic data integration approaches for diagnostic biomarker discovery in any field of the life sciences; • Innovative approaches for the analysis and the visualization of multi-omic datasets; • Methods and applications for systematic measurements from single/undivided samples (comprising genomic, transcriptomic, proteomic, metabolomic measurements, among others); • Multi-scale approaches for integrated dynamic modelling and simulation; • Implementation of applications, computational resources and repositories devoted to data integration including, but not limited to, data warehousing, database federation, semantic integration, service-oriented and/or wiki integration; • Issues related to the definition and implementation of standards, shared identities and semantics, with particular focus on the integration problem. Research papers, reviews and short communications on all topics related to the above issues were welcomed.

Author : Manish Kumar Gupta
Publisher : Elsevier
Page : 434 pages
File Size : 24,95 MB
Release : 2024-05-10
Category : Science
ISBN : 0443160937

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Integrative Omics: Concepts, Methodology and Applications provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference includes a range of chapters in a systemic ‘step by step’ manner, which begins with the basic concepts from Omic to Multi Integrative Omics approaches, followed by their full range of approaches, applications, emerging trends, and future trends. All key areas of Omics are covered including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics as well as omics technology policy and society research. Integrative Omics: Concepts, Methodology and Applications highlights the recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science. The book bridges the gap between biological sciences, physical sciences, computer science, statistics, data science, information technology and mathematics by presenting content specifically dedicated to mathematical models of biological systems. Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to ‘translational research’, i.e., drug discovery, drug target prediction, and precision medicine Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways

Author : Ramesh Namdeo Pudake
Publisher : Springer Nature
Page : 279 pages
File Size : 48,82 MB
Release : 2021-05-08
Category : Science
ISBN : 981160889X

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This book presents a timely review of the latest advances in rhizosphere biology, which have been facilitated by the application of omics tools. It includes chapters on the use of various omics tools in rhizosphere biology, focusing on understanding plant and soil microbe interactions. The role of proteomics and metagenomics in research on symbiotic association is also discussed in detail. The book also includes chapters on the use of omics tools for the isolation of functional biomolecules from rhizospheric microorganisms. The book’s respective sections describe and provide detailed information on important omics tools, such as genomics, transcriptomics, proteomics, metabolomics and meta-epigenomics. In turn, the book promotes and describes the combined use of plant biology, microbial ecology, and soil sciences to design new research strategies and innovative methods in soil biology. Lastly, it highlights the considerable potential of the rhizosphere in terms of crop productivity, bioremediation, ecological engineering, plant nutrition and health, as well as plant adaptation to stress conditions. This book offers both a practical guide and reference source for all scientists working in soil biology, plant pathology, etc. It will also benefit students studying soil microbiology, and researchers studying rhizosphere structure.

Author : Cedric Gondro
Publisher : Springer
Page : 283 pages
File Size : 46,81 MB
Release : 2015-05-18
Category : Medical
ISBN : 3319144758

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Through this book, researchers and students will learn to use R for analysis of large-scale genomic data and how to create routines to automate analytical steps. The philosophy behind the book is to start with real world raw datasets and perform all the analytical steps needed to reach final results. Though theory plays an important role, this is a practical book for graduate and undergraduate courses in bioinformatics and genomic analysis or for use in lab sessions. How to handle and manage high-throughput genomic data, create automated workflows and speed up analyses in R is also taught. A wide range of R packages useful for working with genomic data are illustrated with practical examples. The key topics covered are association studies, genomic prediction, estimation of population genetic parameters and diversity, gene expression analysis, functional annotation of results using publically available databases and how to work efficiently in R with large genomic datasets. Important principles are demonstrated and illustrated through engaging examples which invite the reader to work with the provided datasets. Some methods that are discussed in this volume include: signatures of selection, population parameters (LD, FST, FIS, etc); use of a genomic relationship matrix for population diversity studies; use of SNP data for parentage testing; snpBLUP and gBLUP for genomic prediction. Step-by-step, all the R code required for a genome-wide association study is shown: starting from raw SNP data, how to build databases to handle and manage the data, quality control and filtering measures, association testing and evaluation of results, through to identification and functional annotation of candidate genes. Similarly, gene expression analyses are shown using microarray and RNAseq data. At a time when genomic data is decidedly big, the skills from this book are critical. In recent years R has become the de facto tool for analysis of gene expression data, in addition to its prominent role in analysis of genomic data. Benefits to using R include the integrated development environment for analysis, flexibility and control of the analytic workflow. Included topics are core components of advanced undergraduate and graduate classes in bioinformatics, genomics and statistical genetics. This book is also designed to be used by students in computer science and statistics who want to learn the practical aspects of genomic analysis without delving into algorithmic details. The datasets used throughout the book may be downloaded from the publisher’s website.

Author : Mowafa Househ
Publisher : Springer
Page : 144 pages
File Size : 27,10 MB
Release : 2019-02-26
Category : Medical
ISBN : 3030061094

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This is the first book to offer a comprehensive yet concise overview of the challenges and opportunities presented by the use of big data in healthcare. The respective chapters address a range of aspects: from health management to patient safety; from the human factor perspective to ethical and economic considerations, and many more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applications, the book not only sheds light on the problems entailed by big data, but also paves the way for possible solutions and future research directions. Accordingly, it offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes; and for students and researchers whose work involves data science-related research issues in healthcare.