The Fundamentals Of Modern Statistical Genetics
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The Fundamentals Of Modern Statistical Genetics
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Author : Nan M. Laird
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-12-13
The Fundamentals Of Modern Statistical Genetics written by Nan M. Laird and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-13 with Medical categories.
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.
The Fundamentals Of Modern Statistical Genetics
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Author : Nan M. Laird
language : en
Publisher:
Release Date : 2011-03-30
The Fundamentals Of Modern Statistical Genetics written by Nan M. Laird and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-30 with categories.
Heterogeneity In Statistical Genetics
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Author : Derek Gordon
language : en
Publisher: Springer Nature
Release Date : 2020-12-16
Heterogeneity In Statistical Genetics written by Derek Gordon and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Medical categories.
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.
Fundamentals Of Modern Statistical Genetics
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Author : Tao He
language : en
Publisher:
Release Date : 2016-04
Fundamentals Of Modern Statistical Genetics written by Tao He and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04 with categories.
Fundamentals Of Modern Statistical Methods
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Author : Rand R. Wilcox
language : en
Publisher: Springer
Release Date : 2010-03-10
Fundamentals Of Modern Statistical Methods written by Rand R. Wilcox and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-10 with Social Science categories.
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.
Precision Medicine In Stroke
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Author : Ana Catarina Fonseca
language : en
Publisher: Springer Nature
Release Date : 2021-05-04
Precision Medicine In Stroke written by Ana Catarina Fonseca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-04 with Medical categories.
This book provides a comprehensive coverage of the state of the art in precision medicine in stroke. It starts by explaining and giving general information about precision medicine. Current applications in different strokes types (ischemic, haemorrhagic) are presented from diagnosis to treatment. In addition, ongoing research in the field (early stroke diagnosis and estimation of prognosis) is extensively discussed. The final part provides an in-depth discussion of how different interdisciplinary areas like artificial intelligence, molecular biology and genetics are contributing to this area. Precision Medicine in Stroke provides a practical approach to each chapter, reinforcing clinical applications and presenting clinical cases. This book is intended for all clinicians that interact with stroke patients (neurologists, internal medicine doctors, general practitioners, neurosurgeons), students and basic researchers.
Compositional Data Analysis
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Author : Josep Antoni Martín-Fernández
language : en
Publisher: Springer
Release Date : 2016-11-19
Compositional Data Analysis written by Josep Antoni Martín-Fernández and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-19 with Mathematics categories.
The authoritative contributions gathered in this volume reflect the state of the art in compositional data analysis (CoDa). The respective chapters cover all aspects of CoDa, ranging from mathematical theory, statistical methods and techniques to its broad range of applications in geochemistry, the life sciences and other disciplines. The selected and peer-reviewed papers were originally presented at the 6th International Workshop on Compositional Data Analysis, CoDaWork 2015, held in L’Escala (Girona), Spain. Compositional data is defined as vectors of positive components and constant sum, and, more generally, all those vectors representing parts of a whole which only carry relative information. Examples of compositional data can be found in many different fields such as geology, chemistry, economics, medicine, ecology and sociology. As most of the classical statistical techniques are incoherent on compositions, in the 1980s John Aitchison proposed the log-ratio approach to CoDa. This became the foundation of modern CoDa, which is now based on a specific geometric structure for the simplex, an appropriate representation of the sample space of compositional data. The International Workshops on Compositional Data Analysis offer a vital discussion forum for researchers and practitioners concerned with the statistical treatment and modelling of compositional data or other constrained data sets and the interpretation of models and their applications. The goal of the workshops is to summarize and share recent developments, and to identify important lines of future research.
Principles Of Statistical Genomics
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Author : Shizhong Xu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-13
Principles Of Statistical Genomics written by Shizhong Xu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-13 with Science categories.
Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach. Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data. Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics.
Applied Statistical Genetics With R
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Author : Andrea S. Foulkes
language : en
Publisher: Springer
Release Date : 2009-04-17
Applied Statistical Genetics With R written by Andrea S. Foulkes and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-17 with Science categories.
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.
Stochastic Geometry Spatial Statistics And Random Fields
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Author : Volker Schmidt
language : en
Publisher: Springer
Release Date : 2014-10-24
Stochastic Geometry Spatial Statistics And Random Fields written by Volker Schmidt and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-24 with Mathematics categories.
This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.