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Author : Silke Schmidt
Publisher :
ISBN 13 :
Total Pages : 143 pages
Book Rating : 4.:/5 (722 download)
Download or read book Statistical Methods to Assess Gene-environment written by Silke Schmidt and published by . This book was released on 1999 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sumiko Anno
Publisher : CRC Press
ISBN 13 : 9814669644
Total Pages : 208 pages
Book Rating : 4.8/5 (146 download)
Download or read book Gene-Environment Interaction Analysis written by Sumiko Anno and published by CRC Press. This book was released on 2016-03-30 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gene-environment (GE) interaction analysis is a statistical method for clarifying GE interactions applicable to a phenotype or a disease that is the result of interactions between genes and the environment. This book is the first to deal with the theme of GE interaction analysis. It compiles and details cutting-edge research in bioinformatics
Author : Philip C. Cooley
Publisher : RTI Press
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4./5 ( download)
Download or read book Assessing Gene-Environment Interactions in Genome-Wide Association Studies: Statistical Approaches written by Philip C. Cooley and published by RTI Press. This book was released on 2014-05-14 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report, we address a scenario that uses synthetic genotype case-control data that is influenced by environmental factors in a genome-wide association study (GWAS) context. The precise way the environmental influence contributes to a given phenotype is typically unknown. Therefore, our study evaluates how to approach a GWAS that may have an environmental component. Specifically, we assess different statistical models in the context of a GWAS to make association predictions when the form of the environmental influence is questionable. We used a simulation approach to generate synthetic data corresponding to a variety of possible environmental-genetic models, including a “main effects only” model as well as a “main effects with interactions” model. Our method takes into account the strength of the association between phenotype and both genotype and environmental factors, but we focus on low-risk genetic and environmental risks that necessitate using large sample sizes (N = 10,000 and 200,000) to predict associations with high levels of confidence. We also simulated different Mendelian gene models, and we analyzed how the collection of factors influences statistical power in the context of a GWAS. Using simulated data provides a “truth set” of known outcomes such that the association-affecting factors can be unambiguously determined. We also test different statistical methods to determine their performance properties. Our results suggest that the chances of predicting an association in a GWAS is reduced if an environmental effect is present and the statistical model does not adjust for that effect. This is especially true if the environmental effect and genetic marker do not have an interaction effect. The functional form of the statistical model also matters. The more accurately the form of the environmental influence is portrayed by the statistical model, the more accurate the prediction will be. Finally, even with very large samples sizes, association predictions involving recessive markers with low risk can be poor
Author : Duncan C. Thomas
Publisher : Oxford University Press
ISBN 13 : 0199748055
Total Pages : 458 pages
Book Rating : 4.1/5 (997 download)
Download or read book Statistical Methods in Genetic Epidemiology written by Duncan C. Thomas and published by Oxford University Press. This book was released on 2004-01-29 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Philip Chester Cooley
Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.:/5 (18 download)
Download or read book Assessing Gene-environment Interactions in Genome-wide Association Studies written by Philip Chester Cooley and published by . This book was released on 2014 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this report, we address a scenario that uses synthetic genotype case-control data that is influenced by environmental factors in a genome-wide association study (GWAS) context. The precise way the environmental influence contributes to a given phenotype is typically unknown. Therefore, our study evaluates how to approach a GWAS that may have an environmental component. Specifically, we assess different statistical models in the context of a GWAS to make association predictions when the form of the environmental influence is questionable. We used a simulation approach to generate synthetic data corresponding to a variety of possible environmental-genetic models, including a "main effects only" model as well as a "main effects with interactions" model. Our method takes into account the strength of the association between phenotype and both genotype and environmental factors, but we focus on low-risk genetic and environmental risks that necessitate using large sample sizes (N = 10,000 and 200,000) to predict associations with high levels of confidence. We also simulated different Mendelian gene models, and we analyzed how the collection of factors influences statistical power in the context of a GWAS. Using simulated data provides a "truth set" of known outcomes such that the association-affecting factors can be unambiguously determined. We also test different statistical methods to determine their performance properties. Our results suggest that the chances of predicting an association in a GWAS is reduced if an environmental effect is present and the statistical model does not adjust for that effect. This is especially true if the environmental effect and genetic marker do not have an interaction effect. The functional form of the statistical model also matters. The more accurately the form of the environmental influence is portrayed by the statistical model, the more accurate the prediction will be. Finally, even with very large samples sizes, association predictions involving recessive markers with low risk can be poor.
Author : Hui Jiang
Publisher : MDPI
ISBN 13 : 3039361406
Total Pages : 136 pages
Book Rating : 4.0/5 (393 download)
Download or read book Statistical Methods for the Analysis of Genomic Data written by Hui Jiang and published by MDPI. This book was released on 2020-12-29 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.
Author : Melinda C. Mills
Publisher : MIT Press
ISBN 13 : 0262538385
Total Pages : 433 pages
Book Rating : 4.2/5 (625 download)
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.
Author : M.C. Yang
Publisher : CRC Press
ISBN 13 : 9789056991340
Total Pages : 264 pages
Book Rating : 4.9/5 (913 download)
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.
Author : Cen Wu
Publisher :
ISBN 13 : 9781303310836
Total Pages : 117 pages
Book Rating : 4.3/5 (18 download)
Download or read book High Dimensional Statistical Methods for Gene-environment Interactions written by Cen Wu and published by . This book was released on 2013 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Institute of Medicine
Publisher : National Academies Press
ISBN 13 : 0309101964
Total Pages : 385 pages
Book Rating : 4.3/5 (91 download)
Download or read book Genes, Behavior, and the Social Environment written by Institute of Medicine and published by National Academies Press. This book was released on 2006-12-07 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, we have made great strides in reducing rates of disease and enhancing people's general health. Public health measures such as sanitation, improved hygiene, and vaccines; reduced hazards in the workplace; new drugs and clinical procedures; and, more recently, a growing understanding of the human genome have each played a role in extending the duration and raising the quality of human life. But research conducted over the past few decades shows us that this progress, much of which was based on investigating one causative factor at a time—often, through a single discipline or by a narrow range of practitioners—can only go so far. Genes, Behavior, and the Social Environment examines a number of well-described gene-environment interactions, reviews the state of the science in researching such interactions, and recommends priorities not only for research itself but also for its workforce, resource, and infrastructural needs.
Author : Michael Windle
Publisher : MIT Press
ISBN 13 : 0262335514
Total Pages : 306 pages
Book Rating : 4.2/5 (623 download)
Download or read book Statistical Approaches to Gene x Environment Interactions for Complex Phenotypes written by Michael Windle and published by MIT Press. This book was released on 2016-07-08 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diverse methodological and statistical approaches for investigating the role of gene-environment interactions in a range of complex diseases and traits. Findings from the Human Genome Project and from Genome-Wide Association (GWA) studies indicate that many diseases and traits manifest a more complex genomic pattern than previously assumed. These findings, and advances in high-throughput sequencing, suggest that there are many sources of influence—genetic, epigenetic, and environmental. This volume investigates the role of the interactions of genes and environment (G × E) in diseases and traits (referred to by the contributors as complex phenotypes) including depression, diabetes, obesity, and substance use. The contributors first present different statistical approaches or strategies to address G × E and G × G interactions with high-throughput sequenced data, including two-stage procedures to identify G × E and G × G interactions, marker-set approaches to assessing interactions at the gene level, and the use of a partial-least square (PLS) approach. The contributors then turn to specific complex phenotypes, research designs, or combined methods that may advance the study of G × E interactions, considering such topics as randomized clinical trials in obesity research, longitudinal research designs and statistical models, and the development of polygenic scores to investigate G × E interactions. Contributors Fatima Umber Ahmed, Yin-Hsiu Chen, James Y. Dai, Caroline Y. Doyle, Zihuai He, Li Hsu, Shuo Jiao, Erin Loraine Kinnally, Yi-An Ko, Charles Kooperberg, Seunggeun Lee, Arnab Maity, Jeanne M. McCaffery, Bhramar Mukherjee, Sung Kyun Park, Duncan C. Thomas, Alexandre Todorov, Jung-Ying Tzeng, Tao Wang, Michael Windle, Min Zhang
Author : G. H. Freeman
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (143 download)
Download or read book Statistical methods for the analysis of genotype-environment interactions written by G. H. Freeman and published by . This book was released on 1973 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Nan M. Laird
Publisher : Springer Science & Business Media
ISBN 13 : 1441973389
Total Pages : 226 pages
Book Rating : 4.4/5 (419 download)
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.
Author : Rebecca Hein
Publisher :
ISBN 13 :
Total Pages : 342 pages
Book Rating : 4.:/5 (32 download)
Download or read book Statistical Methods for the Investigation of Gene-environment Interactions in Genetic Epidemiological Acssociation Studies written by Rebecca Hein and published by . This book was released on 2008 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Rebecca Hein
Publisher :
ISBN 13 :
Total Pages : 342 pages
Book Rating : 4.:/5 (699 download)
Download or read book Statistical Methods for the Investigation of Gene-environment Interactions in Genetic Epidemiological Association Studies written by Rebecca Hein and published by . This book was released on 2008 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kenneth Lange
Publisher : Springer Science & Business Media
ISBN 13 : 9780387953892
Total Pages : 404 pages
Book Rating : 4.9/5 (538 download)
Download or read book Mathematical and Statistical Methods for Genetic Analysis written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2003-06-03 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Kenneth Mather
Publisher : Springer
ISBN 13 : 1489934049
Total Pages : 394 pages
Book Rating : 4.4/5 (899 download)
Download or read book Biometrical genetics written by Kenneth Mather and published by Springer. This book was released on 2013-11-11 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: The properties of continuous variation are basic to the theory of evolution and to the practice of plant and animal improvement. Yet the genetical study of continuous variation has lagged far behind that of discontinuous variation. The reason for this situation is basically methodological. Mendel gave us not merely his principles of heredity, but also a method of experiment by which these principles could be tested over a wider range of living species, and extended into the elaborate genetical theory of today. The power of this tool is well attested by the speed with which genetics has grown. In less than fifty years, it has not only developed a theoretical structure which is unique in the biological sciences, but has established a union with nuclear cytology so close that the two have become virtually a single science offering us a new approach to problems so diverse as those of evolution, development, disease, cellular chemistry and human welfare. Much of this progress would have been impossible and all would have been slower without the Mendelian method of recognizing and using unit differences in the genetic materials.
