Biostatistics for Human Genetic Epidemiology


Book Description

The book illustrates how biostatistics may numerically summarize human genetic epidemiology using R, and may be used successfully to solve problems in quantitative Genetic Epidemiology Biostatistics for Human Genetic Epidemiology provides statistical methodologies and R recipes for human genetic epidemiologic problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related human genetic epidemiology, with R codes illustrations for various examples. This clear and concise book covers human genetic epidemiology, using R in data analysis, including multivariate data analysis. It examines probabilistic and statistical theories for modeling human genetic epidemiology – leading the readers through an effective epidemiologic model, from simple to advanced levels. Classical mathematical, probabilistic, and statistical theory are thoroughly discussed and presented. This book also presents R as a calculator and using R in data analysis. Additionally, it covers Advanced Human Genetic Data Concepts, the Study of Human Genetic Variation, Manhattan Plots, as well as the Procedures for Multiple Comparison. Numerous Worked Examples are provided for illustrations of concepts and real-life applications. Biostatistics for Human Genetic Epidemiology is an ideal reference for professionals and students in Medicine (particularly in Preventive Medicine and Public Health Medical Practices), as well as in Genetics, Epidemiology, and Biostatistics.




Statistical Methods in Genetic Epidemiology


Book Description

This well-organized and clearly written text has a unique focus on methods of identifying the joint effects of genes and environment on disease patterns. It follows the natural sequence of research, taking readers through the study designs and statistical analysis techniques for determining whether a trait runs in families, testing hypotheses about whether a familial tendency is due to genetic or environmental factors or both, estimating the parameters of a genetic model, localizing and ultimately isolating the responsible genes, and finally characterizing their effects in the population. Examples from the literature on the genetic epidemiology of breast and colorectal cancer, among other diseases, illustrate this process. Although the book is oriented primarily towards graduate students in epidemiology, biostatistics and human genetics, it will also serve as a comprehensive reference work for researchers. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics will help make the book accessible to those coming from one of these fields without a background in the others. It strikes a good balance between epidemiologic study designs and statistical methods of data analysis.




Biostatistical Genetics and Genetic Epidemiology


Book Description

Human Genetics concerns the study of genetic forces in man. By studying our genetic make-up we are able to understand more about our heritage and evolution. Some of the original, and most significant research in genetics centred around the study of the genetics of complex diseases - genetic epidemiology. This is the third in a highly successful series of books based on articles from the Encyclopedia of Biostatistics. This volume will be a timely and comprehensive reference, for a subject that has seen a recent explosion of interest following the completion of the first draft of the Human Genome Mapping Project. The editors have updated the articles from the Human Genetics section of the EoB, have adpated other articles to give them a genetic feel, and have included a number of newly commissioned articles to ensure the work is comprehensive and provides a self-contained reference.




Basic Biostatistics for Geneticists and Epidemiologists


Book Description

Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful Essentials of Biostatistics has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures. This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes’ theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text. Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.




An Introduction to Genetic Epidemiology


Book Description

This book brings together leading experts to provide an introduction to genetic epidemiology that begins with a primer in human molecular genetics through all the standard methods in population genetics and genetic epidemiology required for an adequate grounding in the field.




Human Genome Epidemiology, 2nd Edition


Book Description

The first edition of Human Genome Epidemiology, published in 2004, discussed how the epidemiologic approach provides an important scientific foundation for studying the continuum from gene discovery to the development, applications and evaluation of human genome information in improving health and preventing disease. Since that time, advances in human genomics have continued to occur at a breathtaking pace.With contributions from leaders in the field from around the world, this new edition is a fully updated look at the ways in which genetic factors in common diseases are studied. Methodologic developments in collection, analysis and synthesis of data, as well as issues surrounding specific applications of human genomic information for medicine and public health are all discussed. In addition, the book focuses on practical applications of human genome variation in clinical practice and disease prevention. Students, clinicians, public health professionals and policy makers will find the book a useful tool for understanding the rapidly evolving methods of the discovery and use of genetic information in medicine and public health in the 21st century.




Biostatistics for Epidemiology and Public Health Using R


Book Description

Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-bystep approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems and exercises drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual. KEY FEATURES: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes online student solutions guide and instructor's manual




Fundamentals of Genetic Epidemiology


Book Description

This text integrates the principles, methods and approaches of epidemiology and genetics in the study of disease aetiology. The authors define the central theme of genetic epidemiology as the study of the role of genetic factors and their interaction with environmental factors in the occurrence of disease in populations.




Biostatistics and Epidemiology


Book Description

Biostatistics and Epidemiology/A Primer for Health Professionals offers practical guidelines and gives a concise framework for research and interpretation in the field. In addition to major sections covering statistics and epidemiology, the book includes a comprehensive exploration of scientific methodology, probability, and the clinical trial. The principles and methods described in this book are basic and apply to all medical subspecialties, psychology and education. The primer will be especially useful to public health officials and students looking for an understandable treatment of the subject.




Statistics in Human Genetics


Book Description

Rigorous statistical analysis methods for human genetics application Statistics in Human Genetics explores the statistical analysis methods that are critical to good science. Beginning with a brief review of genes, gene structure, variation, and terminology, the book moves into analysis of segregation, genetic linkage, allelic associations, and continuity for a wide range of conditions. From the classic Hardy-Weinberg equation to advanced modeling, algorithms and more, this book provides authoritative guidance toward methods, analysis, and applications for anyone performing quantitative analysis of human genetics.