Methods In Statistical Genomics

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Handbook of Statistical Genomics

David J. Balding,Ida Moltke,John Marioni
Handbook of Statistical Genomics Book PDF

Author : David J. Balding,Ida Moltke,John Marioni
Publisher : John Wiley & Sons
Page : 1828 pages
File Size : 47,8 Mb
Release : 2019-07-09
Category : Science
ISBN : 9781119429258

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Handbook of Statistical Genomics by David J. Balding,Ida Moltke,John Marioni Pdf

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.

Statistical Genomics

Ewy Mathé,Sean Davis
Statistical Genomics Book PDF

Author : Ewy Mathé,Sean Davis
Publisher : Humana
Page : 0 pages
File Size : 42,5 Mb
Release : 2016-03-24
Category : Medical
ISBN : 1493935763

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Statistical Genomics by Ewy Mathé,Sean Davis Pdf

This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories, common applications, and representative tools for operating on genomic data. Statistical Genomics: Methods and Protocols is divided into four sections. The first section discusses overview material and resources that can be applied across topics mentioned throughout the book. The second section covers prominent public repositories for genomic data. The third section presents several different biological applications of statistical genomics, and the fourth section highlights software tools that can be used to facilitate ad-hoc analysis and data integration. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible analysis protocols, and tips on troubleshooting and avoiding known pitfalls. Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.

Principles of Statistical Genomics

Shizhong Xu
Principles of Statistical Genomics Book PDF

Author : Shizhong Xu
Publisher : Springer Science & Business Media
Page : 428 pages
File Size : 52,9 Mb
Release : 2012-09-10
Category : Science
ISBN : 9780387708065

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Principles of Statistical Genomics by Shizhong Xu Pdf

Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach. Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data. Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics.

Handbook of Statistical Genetics

David J. Balding,Martin Bishop,Chris Cannings
Handbook of Statistical Genetics Book PDF

Author : David J. Balding,Martin Bishop,Chris Cannings
Publisher : John Wiley & Sons
Page : 1616 pages
File Size : 41,6 Mb
Release : 2008-06-10
Category : Science
ISBN : 0470997621

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Handbook of Statistical Genetics by David J. Balding,Martin Bishop,Chris Cannings Pdf

The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.

Handbook of Statistical Genomics

David J. Balding,Ida Moltke,John Marioni
Handbook of Statistical Genomics Book PDF

Author : David J. Balding,Ida Moltke,John Marioni
Publisher : John Wiley & Sons
Page : 1223 pages
File Size : 54,8 Mb
Release : 2019-09-10
Category : Science
ISBN : 9781119429142

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Handbook of Statistical Genomics by David J. Balding,Ida Moltke,John Marioni Pdf

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.

Statistical Genomics

Ben Hui Liu
Statistical Genomics Book PDF

Author : Ben Hui Liu
Publisher : CRC Press
Page : 642 pages
File Size : 41,6 Mb
Release : 2017-11-22
Category : Mathematics
ISBN : 9781351414531

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Statistical Genomics by Ben Hui Liu Pdf

Genomics, the mapping of the entire genetic complement of an organism, is the new frontier in biology. This handbook on the statistical issues of genomics covers current methods and the tried-and-true classical approaches.

Methods in Statistical Genomics

Philip Chester Cooley
Methods in Statistical Genomics Book PDF

Author : Philip Chester Cooley
Publisher : RTI Press
Page : 163 pages
File Size : 44,6 Mb
Release : 2016-08-29
Category : Medical
ISBN : 9781934831168

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Methods in Statistical Genomics by Philip Chester Cooley Pdf

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.

An Introduction to Statistical Genetic Data Analysis

Melinda C. Mills,Nicola Barban,Felix C. Tropf
An Introduction to Statistical Genetic Data Analysis Book PDF

Author : Melinda C. Mills,Nicola Barban,Felix C. Tropf
Publisher : MIT Press
Page : 433 pages
File Size : 49,5 Mb
Release : 2020-02-18
Category : Science
ISBN : 9780262357449

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An Introduction to Statistical Genetic Data Analysis by Melinda C. Mills,Nicola Barban,Felix C. Tropf Pdf

A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.

Statistical Genomics: Methods and Protocols

Ewy Mathe,Sean Davis
Statistical Genomics Methods and Protocols Book PDF

Author : Ewy Mathe,Sean Davis
Publisher : Methods in Molecular Biology
Page : 432 pages
File Size : 51,6 Mb
Release : 2018-04-07
Category : Medical
ISBN : 1493980831

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Statistical Genomics: Methods and Protocols by Ewy Mathe,Sean Davis Pdf

This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories, common applications, and representative tools for operating on genomic data. Statistical Genomics: Methods and Protocols is divided into four sections. The first section discusses overview material and resources that can be applied across topics mentioned throughout the book. The second section covers prominent public repositories for genomic data. The third section presents several different biological applications of statistical genomics, and the fourth section highlights software tools that can be used to facilitate ad-hoc analysis and data integration. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible analysis protocols, and tips on troubleshooting and avoiding known pitfalls. Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.

Statistical Population Genomics

Julien Y Dutheil
Statistical Population Genomics Book PDF

Author : Julien Y Dutheil
Publisher : Unknown
Page : 464 pages
File Size : 53,6 Mb
Release : 2020-10-08
Category : Science
ISBN : 1013271408

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Statistical Population Genomics by Julien Y Dutheil Pdf

This open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, pointers to the relevant literature, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Statistical Population Genomics aims to promote and ensure successful applications of population genomic methods to an increasing number of model systems and biological questions. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

The Fundamentals of Modern Statistical Genetics

Nan M. Laird,Christoph Lange
The Fundamentals of Modern Statistical Genetics Book PDF

Author : Nan M. Laird,Christoph Lange
Publisher : Springer Science & Business Media
Page : 226 pages
File Size : 49,8 Mb
Release : 2010-12-13
Category : Medical
ISBN : 9781441973382

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The Fundamentals of Modern Statistical Genetics by Nan M. Laird,Christoph Lange Pdf

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.

Heterogeneity in Statistical Genetics

Derek Gordon,Stephen J. Finch,Wonkuk Kim
Heterogeneity in Statistical Genetics Book PDF

Author : Derek Gordon,Stephen J. Finch,Wonkuk Kim
Publisher : Springer Nature
Page : 366 pages
File Size : 40,6 Mb
Release : 2020-12-16
Category : Medical
ISBN : 9783030611217

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Heterogeneity in Statistical Genetics by Derek Gordon,Stephen J. Finch,Wonkuk Kim Pdf

Heterogeneity, or mixtures, are ubiquitous in genetics. Even for data as simple as mono-genic diseases, populations are a mixture of affected and unaffected individuals. Still, most statistical genetic association analyses, designed to map genes for diseases and other genetic traits, ignore this phenomenon. In this book, we document methods that incorporate heterogeneity into the design and analysis of genetic and genomic association data. Among the key qualities of our developed statistics is that they include mixture parameters as part of the statistic, a unique component for tests of association. A critical feature of this work is the inclusion of at least one heterogeneity parameter when performing statistical power and sample size calculations for tests of genetic association. We anticipate that this book will be useful to researchers who want to estimate heterogeneity in their data, develop or apply genetic association statistics where heterogeneity exists, and accurately evaluate statistical power and sample size for genetic association through the application of robust experimental design.

Computational Genomics with R

Altuna Akalin
Computational Genomics with R Book PDF

Author : Altuna Akalin
Publisher : CRC Press
Page : 462 pages
File Size : 40,9 Mb
Release : 2020-12-16
Category : Mathematics
ISBN : 9781498781862

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Computational Genomics with R by Altuna Akalin Pdf

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Osval Antonio Montesinos López,Abelardo Montesinos López,José Crossa
Multivariate Statistical Machine Learning Methods for Genomic Prediction Book PDF

Author : Osval Antonio Montesinos López,Abelardo Montesinos López,José Crossa
Publisher : Springer Nature
Page : 707 pages
File Size : 41,7 Mb
Release : 2022-02-14
Category : Technology & Engineering
ISBN : 9783030890100

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Multivariate Statistical Machine Learning Methods for Genomic Prediction by Osval Antonio Montesinos López,Abelardo Montesinos López,José Crossa Pdf

This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

Mathematical and Statistical Methods for Genetic Analysis

Kenneth Lange
Mathematical and Statistical Methods for Genetic Analysis Book PDF

Author : Kenneth Lange
Publisher : Springer Science & Business Media
Page : 376 pages
File Size : 45,5 Mb
Release : 2012-12-06
Category : Medical
ISBN : 9780387217505

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Mathematical and Statistical Methods for Genetic Analysis by Kenneth Lange Pdf

Written to equip students in the mathematical siences to understand and model the epidemiological and experimental data encountered in genetics research. This second edition expands the original edition by over 100 pages and includes new material. Sprinkled throughout the chapters are many new problems.