Download or read book The Fundamentals of Modern Statistical Genetics written by Nan M. Laird and published by Springer Science & Business Media. This book was released on 2010-12-13 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Fundamentals of Modern Statistical Genetics written by Nan M. Laird and published by . This book was released on 2011-03-30 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fundamentals of Modern Statistical Genetics written by Tao He and published by . This book was released on 2016-04 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Statistical Methods in Modern Genetics written by M.C. Yang and published by CRC Press. This book was released on 2000-02-23 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the basic statistical theory behind modern genetics is not very difficult, most statistical genetics papers are not easy to read for beginners in the field, and formulae quickly become very tedious to fit a particular area of application. Introduction to Statistical Methods in Modern Genetics distinguishes between the necessary and unnecessary complexity in a presentation designed for graduate-level statistics students. The author keeps derivations simple, but does so without losing the mathematical details. He also provides the required background in modern genetics for those looking forward to entering this arena. Along with some of the statistical tools important in genetics applications, students will learn: How a gene is found How scientists have separated the genetic and environmental aspects of a person's intelligence How genetics are used in agriculture to improve crops and domestic animals What a DNA fingerprint is and why there are controversies about it Although the author assumes students have a foundation in basic statistics, an appendix provides the necessary background beyond the elementary, including multinomial distributions, inference on frequency tables, and discriminant analysis. With clear explanations, a multitude of figures, and exercise sets in each chapter, this text forms an outstanding entrée into the rapidly expanding world of genetic data analysis.
Download or read book Applied Statistical Genetics with R written by Andrea S. Foulkes and published by Springer Science & Business Media. This book was released on 2009-04-28 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fundamentals of Modern Statistical Methods written by Rand R. Wilcox and published by Springer Science & Business Media. This book was released on 2010-03-18 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conventional statistical methods have a very serious flaw. They routinely miss differences among groups or associations among variables that are detected by more modern techniques, even under very small departures from normality. Hundreds of journal articles have described the reasons standard techniques can be unsatisfactory, but simple, intuitive explanations are generally unavailable. Situations arise where even highly nonsignificant results become significant when analyzed with more modern methods. Without assuming the reader has any prior training in statistics, Part I of this book describes basic statistical principles from a point of view that makes their shortcomings intuitive and easy to understand. The emphasis is on verbal and graphical descriptions of concepts. Part II describes modern methods that address the problems covered in Part I. Using data from actual studies, many examples are included to illustrate the practical problems with conventional procedures and how more modern methods can make a substantial difference in the conclusions reached in many areas of statistical research. The second edition of this book includes a number of advances and insights that have occurred since the first edition appeared. Included are new results relevant to medians, regression, measures of association, strategies for comparing dependent groups, methods for dealing with heteroscedasticity, and measures of effect size.
Download or read book An Introduction to Statistical Genetic Data Analysis written by Melinda C. Mills and published by MIT Press. This book was released on 2020-02-18 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Handbook of Statistical Genetics written by David J. Balding and published by Wiley. This book was released on 2003-09-19 with total page 1308 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the Reviews of the First Edition: "This magnificent book attempts to catalogue and introduce all aspects of modern statistical genetics...I can thoroughly recommend it." Short Book Reviews of ISI "...extremely well written and referenced work, which must come highly recommended..." Statistical Methods in Medical Research Provides comprehensive coverage of a thriving area of research Features nine newly commissioned chapters All existing chapters have been fully updated with new advances in the field and new references Now includes a glossary of terms, and a list of acronyms and abbreviations. Features extensive cross-referencing between chapters. Each chapter is written by a leading international authority from the field. Complemented by examples, case studies, and references to useful resources on the web.
Download or read book Statistical Genetics written by Prem Narain (Prof.) and published by . This book was released on 1990 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Book Describes The Methodology Of A Field Of Biology That Weds Statistics And Genetics And Goes By The Name Of Statistical Genetics. The Relevant Principles Of Genetics, Statistics And Breeding Are Discussed Together At One Place. The Emphasis Is On The Important Applications Of The Statisticogenetic Principles To The Plant And Animal Breeding Problems. It Has Been Written For The Benefit Of Post- Graduate Students Majoring In The Fields Of Either Genetics And Breeding Or Statistics Applied To Agriculture. Also, Since Advanced Researches In This Field Which Have Taken Place Over The Years Are Scattered In Various Journals, This Book Is Equally Addressed To Researchers In The Fields Of Statistics, Genetics And Breeding.The Book Is Unique In Several Respects And Sets Itself Apart When Compared With Other Published Books On The Subject. The Basic Elements Of Mendelian Genetics Which Is Very Crucial To The Understanding Of The Subject Have Been Included Right In The Beginning. The Relevant Topics Of Population Genetics Essential For Understanding The Principles Of Quantitative Inheritance Have Also Been Dealt With. Special Treatment Has Been Given To The Topics Dealing With The Methods Of Selection And Crossbreeding Which Can Bring About Desired Genetic Improvement. Diallel And Partial Diallel Crosses, Both The Design As Well As The Analysis Aspects Have Been Included.Because Of The Inter-Disciplinary Nature Of The Subject, Bringinng In So To Say Biology And Mathematics Together, The Book Has Adopted An Integrated Approach Placing Due Emphasis On Both The Fields. Appropriate Mathematical And Statistical Derivations For Mathematically Oriented Readers As Also Concepts In Non- Mathematical Terms For Biologist Friends Have Been Presented In A Judicious Manner.
Download or read book An Introduction to Statistical Genetic Data Analysis written by Melinda C. Mills and published by MIT Press. This book was released on 2020-02-18 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Basics of Modern Statistical Genetics written by Linda Lait and published by Delve Publishing. This book was released on 2016-11-30 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines a number of novel techniques used to study populations, phenotypes, and gene expression in organisms as diverse as humans and plants. The book ends with three case studies applying statistical genetics to identify genes associated with human diseases.
Download or read book Modern Statistics for Modern Biology written by SUSAN. HUBER HOLMES (WOLFGANG.) and published by Cambridge University Press. This book was released on 2018 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modern Statistical Methods for Astronomy written by Eric D. Feigelson and published by Cambridge University Press. This book was released on 2012-07-12 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Statistical Methods for Astronomy: With R Applications.
Download or read book Handbook of Statistical Genetics written by David J. Balding and published by John Wiley & Sons. This book was released on 2008-06-10 with total page 1616 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Heterogeneity in Statistical Genetics written by Derek Gordon and published by Springer Nature. This book was released on 2020-12-16 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Advances in Genetic Statistics written by Basavarajaiah D M and published by Educreation Publishing. This book was released on 2017-11-25 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on genetic statistics and quantitative genetics. These books expect different level of preparedness and analytical interventions emphasis on the formulation of real breeding data sets. This book is not introductory, it presumes various statistical and mathematical models demonstrated and derived considering by real breeding data sets. Reader are expected to know the essential of recent statistical tools such as sensor fusion estimation techniques, Kernel regression model, mathematical modeling on hardy Weinberg equilibrium, Pham kinetic genetic model, MLE's, OLR, weighted ordinary least square analysis, genetic correlation, heritability tested by advanced statistical tools, extraction of dummy variables from genetic and non-genetic components, random mating probability models, Risk analysis of human hereditary data by Bayesian approach, algorithms of sex linked inherited X-chromosomes, evaluation of pedigree through statistical approach, sex-linked recessive disorder of human population, data reduction techniques by snap shot techniques, Kal man filter estimation of multiple genetic traits, estimation of genetic variance, structural changes of genetic parameters, oscillation of genotypic and environmental variance, linear and nonlinear models etc. The main emphasis of the entire book is derivation of mathematical and statistical models to prove hardy Weinberg equilibrium at large random mating population. The present text book describes salient objectives and practical applicability to learn what methods are available and more importantly, when they should be applied in real life .Many examples are presented to clarify the use of the recent statistical techniques and to demonstrate what conclusions can be made at the right time modeling on genetics. Nevertheless, Statistical & mathematical modeling is a diversified area including many different topics illustrated by real breeding data sets. Furthermore, an advanced statistical technique has covered in the present edition. As per the genetic model formulation, a new technology is described in all the chapters. The PG students and research Scholars will easily extend the methods to enable for the compilation of high dimensional breeding datasets (Big data) generated from different experimental designs. Although the book narrowly focuses on a few topics, each topic Genetic fundamentals is provided with the partial derivatives. In collective terms, the statistical genetics is a multidisciplinary area with rapid developments, the present text book will helps to breeder's, researcher's and students to solve the real world problems of Genetics. For example, during the time between the completion of the first draft and the publication of this book, new methodologies and model formulation may have already been developed. Therefore, the book can only focus on the principles of advance statistical genetics. The present academic book intends to be used as a textbook for post graduate students in human, plant and animal genetics, but it can also be used by researchers as a reference book. For advanced readers, they can choose to read any particular chapters as they desire.
Download or read book The R Book written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2007-06-13 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
