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Author: Michelle Carlsen Publisher: ISBN: Category : Languages : en Pages :
Book Description
This paper presents improved methods for analysis of genome-wide association studies in contemporary genetic research. Thanks to current sequencing methods, half to one million single-nucleotide polymorphisms (SNPs) can be feasibly generated within any given population, and there are often correlations among SNPs that cause truly causative loci to be confounded by correlated neighboring loci. Additionally, complex traits are often jointly affected by multiple genetic variants with each having small or moderate individual effects. To address these issues in genome-wide association studies, we propose a novel statistical approach, DCRR, to detect significant associations between large numbers of SNPs and phenotypes. We applied DCRR on simulations of that varied in marker allele frequencies, linkage disequilibrium, and the numbers of SNPs considered; and we analyzed a previously published Arabidopsis thaliana dataset of an AvrRpm1 binary trait. Our distance correlation was effective in ranking SNPs while the logistic ridge regression detected causative SNPs without including spurious correlated neighbors. Our results indicate that DCRR is an effective and reliable method that can improve the accuracy and efficiency of large association datasets.
Author: Michelle Carlsen Publisher: ISBN: Category : Languages : en Pages :
Book Description
This paper presents improved methods for analysis of genome-wide association studies in contemporary genetic research. Thanks to current sequencing methods, half to one million single-nucleotide polymorphisms (SNPs) can be feasibly generated within any given population, and there are often correlations among SNPs that cause truly causative loci to be confounded by correlated neighboring loci. Additionally, complex traits are often jointly affected by multiple genetic variants with each having small or moderate individual effects. To address these issues in genome-wide association studies, we propose a novel statistical approach, DCRR, to detect significant associations between large numbers of SNPs and phenotypes. We applied DCRR on simulations of that varied in marker allele frequencies, linkage disequilibrium, and the numbers of SNPs considered; and we analyzed a previously published Arabidopsis thaliana dataset of an AvrRpm1 binary trait. Our distance correlation was effective in ranking SNPs while the logistic ridge regression detected causative SNPs without including spurious correlated neighbors. Our results indicate that DCRR is an effective and reliable method that can improve the accuracy and efficiency of large association datasets.
Author: Andrew R. Collins Publisher: Springer Science & Business Media ISBN: 1597453897 Category : Medical Languages : en Pages : 529
Book Description
As researchers continue to make enormous progress in mapping disease genes, exciting, novel, and complex analyses have emerged. In this book, scientists from around the world, who are leaders in this field, contribute their vast experience and expertise to produce a comprehensive and fascinating text for researchers and clinicians alike. They provide cutting-edge analysis of the most up-to-date and preeminent information available.
Author: Jotun Hein Publisher: Oxford University Press, USA ISBN: 9780191546150 Category : Population genetics Languages : en Pages : 298
Book Description
Authored by leading experts, this seminal text presents a straightforward and elementary account of coalescent theory, which is a central concept in the study of genetic sequence variation observed in a population. Rich in examples and illustrations it is ideal for a graduate course in statistics, population, molecular and medical genetics, bioscience and medicine, and for students studying the evolution of human population and disease. It is also an invaluable reference for bioscientists and statisticians in the pharmaceutical industry and academia - ;Coalescent theory is a central concept in the study of genetic sequence variation that probabilistically describes the genealogy relating the sampled sequences. In this text, besides fulfilling the glaring need for such a book, the authors present this theory in a straightforward and elementary manner and describe the statistical and computational methods used in modelling and analyzing genetic sequence variation. Rich in examples and illustrations the book covers basic concepts, complications arising from geographical structure and recombination before considering aspects of statistical inference based on these models. The book ends with chapters on Gene Mapping, which combines sequence variation data with phenotypic data (such as disease) to define areas of the genome where genes are responsible for the trait, and Human Evolution, a research area that is experiencing a renaissance due to the enormous amounts of data produced in molecular studies. Authored by leading experts, this seminal text presents a straightforward and elementary account of coalescent theory, which is a central concept in the study of genetic sequence variation observed in a population. It is highly suitable for a graduate course in statistics, population, molecular and medical genetics, bioscience and medicine and students studying the evolution of human population and disease, and will be an invaluable reference for bioscientists and statisticians in the pharmaceutical industry and academia - ;an excellent and timely book that should appeal to a variety of people in genetics and applied mathematics. - Professor Montgomery Slatkin (Berkeley);the authors are outstanding experts in the field, and the book is topical and timely. - Professor David Balding (Imperial College);Hein, Schierup and Wiuf have written the first general book on the coalescent. It is an engaging combination of clear mathematical derivation and real data examples. - Professor Joe Felsenstein (University of Washington)
Author: Leo Breiman Publisher: Routledge ISBN: 135146048X Category : Mathematics Languages : en Pages : 370
Book Description
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Author: James F. Holland Publisher: PMPH-USA ISBN: 9781607950141 Category : Medical Languages : en Pages : 2052
Book Description
Holland Frei Cancer Medicine serves as a quick reference to current information on an extensive list of cancers, including breast, lung, thyroid, colorectal, ovarian, prostate, and gastric cancer, to name but a few. Presented as an accessible pocket-sized handbook, the chapters are organized in an outline format, offering only the most essential information on the etiology, staging (including TNM staging) and treatment for each cancer type. Individual chapters are devoted to the molecular biology of cancer, cancer prevention, cancer screening, the mechanisms of chemotherapy, and diagnostic imaging in cancer. Additionally, each chapter lists all the major phase III clinical trials, and therefore, serves as an excellent reference of the major randomized controlled trials for each cancer reported to date. Specific chapters are also dedicated to the discussion of oncologic emergencies, pain and palliation, and prescription complications. At the conclusion of the book, a glossary of oncologic terms and chemotherapeutic drug programs, a table of common cancer incidences, and an overview of the mechanisms, common uses, and related toxicities of various anti-cancer agents are featured. In addition, performance status tables, mathematical formulas and a listing of common biomedical / cancer web sites are highlighted.
Author: Eleftheria Zeggini Publisher: Academic Press ISBN: 0123751438 Category : Medical Languages : en Pages : 353
Book Description
According to the National Institute of Health, a genome-wide association study is defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition. Whole genome information, when combined with clinical and other phenotype data, offers the potential for increased understanding of basic biological processes affecting human health, improvement in the prediction of disease and patient care, and ultimately the realization of the promise of personalized medicine. In addition, rapid advances in understanding the patterns of human genetic variation and maturing high-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to health and disease. This burgeoning science merges the principles of statistics and genetics studies to make sense of the vast amounts of information available with the mapping of genomes. In order to make the most of the information available, statistical tools must be tailored and translated for the analytical issues which are original to large-scale association studies. Analysis of Complex Disease Association Studies will provide researchers with advanced biological knowledge who are entering the field of genome-wide association studies with the groundwork to apply statistical analysis tools appropriately and effectively. With the use of consistent examples throughout the work, chapters will provide readers with best practice for getting started (design), analyzing, and interpreting data according to their research interests. Frequently used tests will be highlighted and a critical analysis of the advantages and disadvantage complimented by case studies for each will provide readers with the information they need to make the right choice for their research. Additional tools including links to analysis tools, tutorials, and references will be available electronically to ensure the latest information is available. Easy access to key information including advantages and disadvantage of tests for particular applications, identification of databases, languages and their capabilities, data management risks, frequently used tests Extensive list of references including links to tutorial websites Case studies and Tips and Tricks
Author: D.C. Rao Publisher: Academic Press ISBN: 0080569110 Category : Medical Languages : en Pages : 788
Book Description
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
Author: Felipe Lopes da Silva Publisher: Springer ISBN: 3319574337 Category : Science Languages : en Pages : 439
Book Description
This book was written by soybean experts to cluster in a single publication the most relevant and modern topics in soybean breeding. It is geared mainly to students and soybean breeders around the world. It is unique since it presents the challenges and opportunities faced by soybean breeders outside the temperate world.
Author: Bo Peng Publisher: John Wiley & Sons ISBN: 1118180348 Category : Science Languages : en Pages : 258
Book Description
The only book available in the area of forward-time population genetics simulations—applicable to both biomedical and evolutionary studies The rapid increase of the power of personal computers has led to the use of serious forward-time simulation programs in genetic studies. Forward-Time Population Genetics Simulations presents both new and commonly used methods, and introduces simuPOP, a powerful and flexible new program that can be used to simulate arbitrary evolutionary processes with unique features like customized chromosome types, arbitrary nonrandom mating schemes, virtual subpopulations, information fields, and Python operators. The book begins with an overview of important concepts and models, then goes on to show how simuPOP can simulate a number of standard population genetics models—with the goal of demonstrating the impact of genetic factors such as mutation, selection, and recombination on standard Wright-Fisher models. The rest of the book is devoted to applications of forward-time simulations in various research topics. Forward-Time Population Genetics Simulations includes: An overview of currently available forward-time simulation methods, their advantages, and shortcomings An overview and evaluation of currently available software A simuPOP tutorial Applications in population genetics Applications in genetic epidemiology, statistical genetics, and mapping complex human diseases The only book of its kind in the field today, Forward-Time Population Genetics Simulations will appeal to researchers and students of population and statistical genetics.
Author: Bruce Walsh Publisher: Oxford University Press ISBN: 0192566644 Category : Science Languages : en Pages : 1504
Book Description
Quantitative traits-be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene-usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences.
Author: Michelle Carlsen
Author: Michelle Carlsen
Author: Andrew R. Collins
Author: Jotun Hein
Author: Leo Breiman
Author: James F. Holland
Author: Eleftheria Zeggini
Author: D.C. Rao
Author: Felipe Lopes da Silva
Author: Bo Peng
Author: Bruce Walsh