Principles Of Statistical Genomics

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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 : 48,5 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.

Statistical Genomics

Ben Hui Liu
Statistical Genomics Book PDF

Author : Ben Hui Liu
Publisher : CRC Press
Page : 642 pages
File Size : 48,6 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.

Applied Statistical Genetics with R

Andrea S. Foulkes
Applied Statistical Genetics with R Book PDF

Author : Andrea S. Foulkes
Publisher : Springer Science & Business Media
Page : 264 pages
File Size : 48,9 Mb
Release : 2009-04-28
Category : Science
ISBN : 9780387895543

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Applied Statistical Genetics with R by Andrea S. Foulkes Pdf

Statistical genetics has become a core course in many graduate programs in public health and medicine. This book presents fundamental concepts and principles in this emerging field at a level that is accessible to students and researchers with a first course in biostatistics. Extensive examples are provided using publicly available data and the open source, statistical computing environment, R.

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 : 43,8 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.

Computational and Statistical Approaches to Genomics

Wei Zhang,Ilya Shmulevich
Computational and Statistical Approaches to Genomics Book PDF

Author : Wei Zhang,Ilya Shmulevich
Publisher : Springer Science & Business Media
Page : 345 pages
File Size : 42,6 Mb
Release : 2002
Category : Mathematics
ISBN : 9781402070235

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Computational and Statistical Approaches to Genomics by Wei Zhang,Ilya Shmulevich Pdf

Computational and Statistical Genomics aims to help researchers deal with current genomic challenges. Topics covered include: overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for microarray data analysis; approaches to the global modeling and analysis of gene regulatory networks and transcriptional control, using methods, theories, and tools from signal processing, machine learning, information theory, and control theory; state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning, applied to cancer classification, identification of biologically active sites, and visualization of gene expression data; crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels in a single cell, statistically sound design of microarray studies and experiments; and biological and medical implications of genomics research.

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 : 44,8 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 Genetics

Benjamin Neale,Manuel Ferreira,Sarah Medland,Danielle Posthuma
Statistical Genetics Book PDF

Author : Benjamin Neale,Manuel Ferreira,Sarah Medland,Danielle Posthuma
Publisher : Garland Science
Page : 608 pages
File Size : 40,7 Mb
Release : 2007-11-30
Category : Science
ISBN : 9781134129331

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Statistical Genetics by Benjamin Neale,Manuel Ferreira,Sarah Medland,Danielle Posthuma Pdf

Statistical Genetics is an advanced textbook focusing on conducting genome-wide linkage and association analysis in order to identify the genes responsible for complex behaviors and diseases. Starting with an introductory section on statistics and quantitative genetics, it covers both established and new methodologies, providing the genetic and statistical theory on which they are based. Each chapter is written by leading researchers, who give the reader the benefit of their experience with worked examples, study design, and sources of error. The text can be used in conjunction with an associated website (www.genemapping.org) that provides supplementary material and links to downloadable software.

Principles of Quantitative Genetics

Wharton B. Mather
Principles of Quantitative Genetics Book PDF

Author : Wharton B. Mather
Publisher : Unknown
Page : 304 pages
File Size : 44,6 Mb
Release : 1964
Category : Biometry
ISBN : LCCN:64011477

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Principles of Quantitative Genetics by Wharton B. Mather Pdf

Statistical genetics; Population genetics; Biometrical genetics.

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 : 45,6 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.

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 : 52,7 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.

Statistical Genetics of Quantitative Traits

Rongling Wu,Changxing Ma,George Casella
Statistical Genetics of Quantitative Traits Book PDF

Author : Rongling Wu,Changxing Ma,George Casella
Publisher : Springer Science & Business Media
Page : 371 pages
File Size : 44,9 Mb
Release : 2007-07-17
Category : Science
ISBN : 9780387681542

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Statistical Genetics of Quantitative Traits by Rongling Wu,Changxing Ma,George Casella Pdf

This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.

Primer to Analysis of Genomic Data Using R

Cedric Gondro
Primer to Analysis of Genomic Data Using R Book PDF

Author : Cedric Gondro
Publisher : Springer
Page : 270 pages
File Size : 42,9 Mb
Release : 2015-05-18
Category : Medical
ISBN : 9783319144757

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Primer to Analysis of Genomic Data Using R by Cedric Gondro Pdf

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.

The Statistics of Gene Mapping

David Siegmund,Benjamin Yakir
The Statistics of Gene Mapping Book PDF

Author : David Siegmund,Benjamin Yakir
Publisher : Springer Science & Business Media
Page : 334 pages
File Size : 43,7 Mb
Release : 2007-05-27
Category : Medical
ISBN : 9780387496863

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The Statistics of Gene Mapping by David Siegmund,Benjamin Yakir Pdf

This book details the statistical concepts used in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. It presents elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic experiments and evaluate statistical analyses. Each chapter contains exercises, both theoretical and computational, some routine and others that are more challenging. The R programming language is developed in the text.

Computational Genome Analysis

Richard C. Deonier,Simon Tavaré,Michael S. Waterman
Computational Genome Analysis Book PDF

Author : Richard C. Deonier,Simon Tavaré,Michael S. Waterman
Publisher : Springer Science & Business Media
Page : 542 pages
File Size : 41,7 Mb
Release : 2005-12-27
Category : Computers
ISBN : 9780387288079

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Computational Genome Analysis by Richard C. Deonier,Simon Tavaré,Michael S. Waterman Pdf

This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.

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 : 277 pages
File Size : 53,8 Mb
Release : 2013-04-17
Category : Mathematics
ISBN : 9781475727395

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Mathematical and Statistical Methods for Genetic Analysis by Kenneth Lange Pdf

Geneticists now stand on the threshold of sequencing the genome in its entirety. The unprecedented insights into human disease and evolution offered by mapping and sequencing are transforming medicine and agriculture. This revolution depends vitally on the contributions made by applied mathematicians, statisticians, and computer scientists. Kenneth Lange has written a book to enable graduate students in the mathematical sciences to understand and model the epidemiological and experimental data encountered in genetics research. Mathematical, statistical, and computational principles relevant to this task are developed hand-in-hand with applications to gene mapping, risk prediction, and the testing of epidemiological hypotheses. The book covers many topics previously only accessible in journal articles, such as pedigree analysis algorithms, Markov chain, Monte Carlo methods, reconstruction of evolutionary trees, radiation hybrid mapping, and models of recombination. The whole is backed by numerous exercise sets.