Insights in Statistical Genetics and Methodology: 2022 PDF Download
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Author: Simon Charles Heath
Publisher: Frontiers Media SA
ISBN: 283253645X
Category : Science
Languages : en
Pages : 172
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Book Description
This Research Topic is part of the Insights in Frontiers in Genetics series.
Author: Simon Charles Heath
Publisher: Frontiers Media SA
ISBN: 283253645X
Category : Science
Languages : en
Pages : 172
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Book Description
This Research Topic is part of the Insights in Frontiers in Genetics series.
Author: Nan M. Laird
Publisher: Springer Science & Business Media
ISBN: 1441973389
Category : Medical
Languages : en
Pages : 226
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Book Description
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: Kenneth Lange
Publisher: Springer Science & Business Media
ISBN: 9780387949093
Category : Genetics
Languages : en
Pages : 0
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Book Description
During the past decade, geneticists have constructed detailed maps of the human genome and cloned scores of Mendelian disease genes. These insights into human disease and evolution which have transformed medicine and agriculture depend on the contributions of applied mathematicians, statisticians, and computer scientists. This work is written to help readers understand and model the epidemiological and experimental data encountered in genetics research.
Author: Richard D. Emes
Publisher: Frontiers Media SA
ISBN: 2832531733
Category : Science
Languages : en
Pages : 195
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Book Description
This Research Topic is part of the Insights in Frontiers in Genetics series. Other titles in the series are: Genetics, Insights in Evolutionary and Population Genetics: 2022 Genetics, Insights in Livestock Genomics: 2022 Genetics, Insights in Epigenomics and Epigenetics: 2022 Genetics, Insights in Behavioral and Psychiatric Genetics: 2022 Genetics, Insights in Neurogenomics: 2022 Genetics, Insights in Genomic Assay Technology: 2022 Genetics, Insights in Genetics of Common and Rare Diseases: 2022 We are now entering the third decade of the 21st Century, and, especially in the last years, the achievements made by scientists have been exceptional, leading to major advancements in the fast-growing field of Genetics. Frontiers have organized a series of Research Topics to highlight the latest advancements in research across the field of Computational Genomics, with articles from the members of our accomplished Editorial Boards. This editorial initiative of particular relevance, led by Prof Richard Emes, Specialty Chief Editor of the Computational Genomics section, together with Dr. Pirooznia and Dr Zou, focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Computational Genomics. The Research Topic solicits brief, forward-looking contributions from the editorial board members that describe the state of the art, outlining recent developments and major accomplishments that have been achieved and that need to occur to move the field forward. Authors are encouraged to identify the greatest challenges in the sub-disciplines, and how to address those challenges.
Author: Andrea S. Foulkes
Publisher: Springer Science & Business Media
ISBN: 038789554X
Category : Science
Languages : en
Pages : 264
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Book Description
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.
Author: Jiajie Peng
Publisher: Frontiers Media SA
ISBN: 2889761746
Category : Science
Languages : en
Pages : 160
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Book Description
Author: Guanglin He
Publisher: Frontiers Media SA
ISBN: 2832513670
Category : Science
Languages : en
Pages : 150
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Author: Yuan-Ming Zhang
Publisher: Frontiers Media SA
ISBN: 2832543693
Category : Science
Languages : en
Pages : 278
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Book Description
Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.
Author: Samuel A. Cushman
Publisher: Frontiers Media SA
ISBN: 2832530133
Category : Science
Languages : en
Pages : 149
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Book Description
Author: Guiyou Liu
Publisher: Frontiers Media SA
ISBN: 2889768287
Category : Science
Languages : en
Pages : 222
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Book Description
