[PDF] Statistical Methods Computing And Resources For Genome Wide Association Studies eBook

Author : Philip Chester Cooley
Publisher : RTI Press
Page : 163 pages
File Size : 45,68 MB
Release : 2016-08-29
Category : Medical
ISBN : 1934831166

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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 Some of the material is unpublished and contains commentary and unpublished research; other chapters (Chapters 4 through 7) have been published in other journals.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.

Author : Nan M. Laird
Publisher : Springer Science & Business Media
Page : 226 pages
File Size : 32,7 MB
Release : 2010-12-13
Category : Medical
ISBN : 1441973389

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This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.

Author : Christopher Austin German
Publisher :
Page : 162 pages
File Size : 45,86 MB
Release : 2021
Category :
ISBN :

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Genome-Wide Association Studies (GWAS) encompass an important area of statistical genetics. They seek to identify single-nucleotide polymorphisms (SNPs) that are associated with a trait of interest. It is becoming more common for large-scale resources of patient data such as biobanks to become available to researchers that include both genetic data and phenotype data from electronic health records (EHR). New techniques for GWAS are necessary to handle both the large sample sizes and the types of complex data generated from these resources. The first chapter aims to tackle both of these issues by establishing an efficient method of conducting a genome-wide scan of SNPs associated with ordinal traits, which commonly occur from phenotyping algorithms for complex diseases. Chapter two focuses on estimating the effects of covariates on intra-individual variances in a framework that can scale to big longitudinal data. Within-subject variances of traits such as blood pressure have been found to be risk factors, independent of mean levels, for a variety of conditions such as cardiovascular disease. We develop a weighted method of moments (MoM) framework for fitting a mixed effects location-scale model that is robust to distributional assumptions and is computationally tractable for biobank-sized data sets. The third chapter uses the framework from the second chapter to develop and conduct large-scale GWAS, identifying variants associated with intra-individual variability of longitudinal traits. In all of these projects, a main focus is ensuring that the methods can scale to the large sample sizes common in biobank data sets.

Author : Daniel O. Stram
Publisher : Springer Science & Business Media
Page : 344 pages
File Size : 37,75 MB
Release : 2013-11-23
Category : Medical
ISBN : 1461494435

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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.

Author : Juan R. González
Publisher : CRC Press
Page : 348 pages
File Size : 38,1 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 : David J. Balding
Publisher : John Wiley & Sons
Page : 1223 pages
File Size : 35,28 MB
Release : 2019-09-10
Category : Science
ISBN : 1119429145

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A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Author : D.C. Rao
Publisher : Academic Press
Page : 788 pages
File Size : 21,60 MB
Release : 2008-04-23
Category : Medical
ISBN : 0080569110

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The field of genetics is rapidly evolving and new medical breakthroughs are occuring as a result of advances in knowledge of genetics. This series continually publishes important reviews of the broadest interest to geneticists and their colleagues in affiliated disciplines. Five sections on the latest advances in complex traits Methods for testing with ethical, legal, and social implications Hot topics include discussions on systems biology approach to drug discovery; using comparative genomics for detecting human disease genes; computationally intensive challenges, and more