Integrative Analysis Of Genome Wide Association Studies And Single Cell Sequencing Studies
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Integrative Analysis Of Genome Wide Association Studies And Single Cell Sequencing Studies
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Author : Sheng Yang
language : en
Publisher: Frontiers Media SA
Release Date : 2021-09-09
Integrative Analysis Of Genome Wide Association Studies And Single Cell Sequencing Studies written by Sheng Yang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-09 with Science categories.
Multimodal And Integrative Analysis Of Single Cell Or Bulk Sequencing Data
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Author : Geng Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2021-04-07
Multimodal And Integrative Analysis Of Single Cell Or Bulk Sequencing Data written by Geng Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-07 with Science categories.
Design Analysis And Interpretation Of Genome Wide Association Scans
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Author : Daniel O. Stram
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-23
Design Analysis And Interpretation Of Genome Wide Association Scans written by Daniel O. Stram and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-23 with Medical categories.
This book presents the statistical aspects of designing, analyzing and interpreting the results of genome-wide association scans (GWAS studies) for genetic causes of disease using unrelated subjects. Particular detail is given to the practical aspects of employing the bioinformatics and data handling methods necessary to prepare data for statistical analysis. The goal in writing this book is to give statisticians, epidemiologists, and students in these fields the tools to design a powerful genome-wide study based on current technology. The other part of this is showing readers how to conduct analysis of the created study. Design and Analysis of Genome-Wide Association Studies provides a compendium of well-established statistical methods based upon single SNP associations. It also provides an introduction to more advanced statistical methods and issues. Knowing that technology, for instance large scale SNP arrays, is quickly changing, this text has significant lessons for future use with sequencing data. Emphasis on statistical concepts that apply to the problem of finding disease associations irrespective of the technology ensures its future applications. The author includes current bioinformatics tools while outlining the tools that will be required for use with extensive databases from future large scale sequencing projects. The author includes current bioinformatics tools while outlining additional issues and needs arising from the extensive databases from future large scale sequencing projects.
Integrative Analysis Of Single Cell And Or Bulk Multi Omics Sequencing Data
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Author : Geng Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-03-13
Integrative Analysis Of Single Cell And Or Bulk Multi Omics Sequencing Data written by Geng Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Science categories.
Methods In Statistical Genomics
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Author : Philip Chester Cooley
language : en
Publisher: RTI Press
Release Date : 2016-08-29
Methods In Statistical Genomics written by Philip Chester Cooley and has been published by RTI Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-29 with Medical categories.
The objective of this book is to describe procedures for analyzing genome-wide association studies (GWAS). Some of the material is unpublished and contains commentary and unpublished research; other chapters (Chapters 4 through 7) have been published in other journals. Each previously published chapter investigates a different genomics model, but all focus on identifying the strengths and limitations of various statistical procedures that have been applied to different GWAS scenarios.
Genome Wide Association Studies
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Author : Krishnarao Appasani
language : en
Publisher: Cambridge University Press
Release Date : 2016-01-14
Genome Wide Association Studies written by Krishnarao Appasani and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-14 with Medical categories.
Experts from academia and industry highlight the potential of genome-wide association studies from basic science to clinical and biotechnological/pharmaceutical applications.
Genome Wide Association Studies
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Author : Tatsuhiko Tsunoda
language : en
Publisher: Springer
Release Date : 2020-11-14
Genome Wide Association Studies written by Tatsuhiko Tsunoda and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-14 with Medical categories.
This book examines the utility of genome-wide association studies (GWAS) in the era of next-generation sequencing and big data, identifies limitations and potential means of overcoming them, and looks to the future of GWAS and what may lay beyond. GWAS are among the most powerful tools for elucidating the genetic aspects of human and disease diversity. In Genome-Wide Association Studies, experts in the field explore in depth the impacts of GWAS on genomic research into a variety of common diseases, including cardiovascular, autoimmune, diabetic, cancer, and infectious diseases. The book will equip readers with a sound understanding both of the types of disease and phenotypes that are suited for GWAS and of the ways in which a road map resulting from GWAS can lead to the realization of personalized/precision medicine: functional analysis, drug seeds, pathway analysis, disease mechanism, risk prediction, and diagnosis.
Computational Methods For Single Cell Data Analysis
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Author : Guo-Cheng Yuan
language : en
Publisher: Humana Press
Release Date : 2019-02-14
Computational Methods For Single Cell Data Analysis written by Guo-Cheng Yuan and has been published by Humana Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-14 with Science categories.
This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.
Next Steps For Functional Genomics
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2020-12-18
Next Steps For Functional Genomics written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with Science categories.
One of the holy grails in biology is the ability to predict functional characteristics from an organism's genetic sequence. Despite decades of research since the first sequencing of an organism in 1995, scientists still do not understand exactly how the information in genes is converted into an organism's phenotype, its physical characteristics. Functional genomics attempts to make use of the vast wealth of data from "-omics" screens and projects to describe gene and protein functions and interactions. A February 2020 workshop was held to determine research needs to advance the field of functional genomics over the next 10-20 years. Speakers and participants discussed goals, strategies, and technical needs to allow functional genomics to contribute to the advancement of basic knowledge and its applications that would benefit society. This publication summarizes the presentations and discussions from the workshop.
Big Data In Omics And Imaging
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Author : Momiao Xiong
language : en
Publisher: CRC Press
Release Date : 2018-06-14
Big Data In Omics And Imaging written by Momiao Xiong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-14 with Mathematics categories.
Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic and imaging data analysis and causal inference in big data era. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), genome-wide expression studies (GWES), and epigenome-wide association studies (EWAS), the overall contribution of the new identified genetic variants is small and a large fraction of genetic variants is still hidden. Understanding the etiology and causal chain of mechanism underlying complex diseases remains elusive. It is time to bring big data, machine learning and causal revolution to developing a new generation of genetic analysis for shifting the current paradigm of genetic analysis from shallow association analysis to deep causal inference and from genetic analysis alone to integrated omics and imaging data analysis for unraveling the mechanism of complex diseases. FEATURES Provides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, epigenomics, medical image, bioinformatics, and data science. Topics covered are: mathematical formulation of causal inference, information geometry for causal inference, topology group and Haar measure, additive noise models, distance correlation, multivariate causal inference and causal networks, dynamic causal networks, multivariate and functional structural equation models, mixed structural equation models, causal inference with confounders, integer programming, deep learning and differential equations for wearable computing, genetic analysis of function-valued traits, RNA-seq data analysis, causal networks for genetic methylation analysis, gene expression and methylation deconvolution, cell –specific causal networks, deep learning for image segmentation and image analysis, imaging and genomic data analysis, integrated multilevel causal genomic, epigenomic and imaging data analysis.