Pedigree Analysis in R covers a wide range of applications in forensic and medical genetics. The book's material was developed through teaching numerous courses on genetic relatedness and pedigree analysis and includes extensive use of R and insights from a decade of research activities in forensic and medical genetics. The Ped Suite, a unified collection of R packages for pedigree analysis, will help users navigate the book's contents. Presents a coherent treatment of a variety of pedigree analyses Treats a variety of pedigree analysis, including theoretical backgrounds, an overview of R features/analysis, an in-depth analysis of a worked examples, exercises, and easy-to-follow R code with explanations
|Author||: U. Hübner,U. Sax,H.-U. Prokosch|
|Publisher||: IOS Press|
|Release Date||: 2018-09-06|
|ISBN 10||: 1614998965|
|Pages||: 260 pages|
Advances in digital and information technology have meant that medical informatics and its associated fields are of ever-increasing importance in the modern healthcare environment. This book presents selected papers from the 63rd annual conference of the German Society of Medical Information Sciences, Biometry, and Epidemiology, GMDS 2018, held in Osnabrück, Germany, in September 2018. The society encompasses not only medical informatics, biometry and epidemiology, but also medical bioinformatics, systems biology and health data management. The title of this year’s conference is “The Learning Health System: Research Based, Innovative, Connecting”, and 38 full papers of the 164 oral presentations and 65 posters delivered at the conference are included here. A wide variety of scientific topics are covered, including standards to enable the interoperable interchange of information; metadata management; record linkage; IT issues for health care networks; interprofessional teaching and training; eHealth legislation; analysis of miRNAs and RNA-Seq data, among others. The contributors are all specialists in their field, and this book disseminates some of the innovative ideas which are urgently needed to meet the challenges facing a constantly developing digital healthcare environment.
Social behavior has long puzzled evolutionary biologists, since the classical theory of natural selection maintains that individuals should not sacrifice their own fitness to affect that of others. Social Evolution and Inclusive Fitness Theory argues that a theory first presented in 1963 by William D. Hamilton—inclusive fitness theory—provides the most fundamental and general explanation for the evolution and maintenance of social behavior in the natural world. James Marshall guides readers through the vast and confusing literature on the evolution of social behavior, introducing and explaining the competing theories that claim to provide answers to questions such as why animals evolve to behave altruistically. Using simple statistical language and techniques that practicing biologists will be familiar with, he provides a comprehensive yet easily understandable treatment of key concepts and their repeated misinterpretations. Particular attention is paid to how more realistic features of behavior, such as nonadditivity and conditionality, can complicate analysis. Marshall highlights the general problem of identifying the underlying causes of evolutionary change, and proposes fruitful approaches to doing so in the study of social evolution. Social Evolution and Inclusive Fitness Theory describes how inclusive fitness theory addresses both simple and complex social scenarios, the controversies surrounding the theory, and how experimental work supports the theory as the most powerful explanation for social behavior and its evolution.
Relationship Inference in Familias and R discusses the use of Familias and R software to understand genetic kinship of two or more DNA samples. This software is commonly used for forensic cases to establish paternity, identify victims or analyze genetic evidence at crime scenes when kinship is involved. The book explores utilizing Familias software and R packages for difficult situations including inbred families, mutations and missing data from degraded DNA. The book additionally addresses identification following mass disasters, familial searching, non-autosomal marker analysis and relationship inference using linked markers. The second part of the book focuses on more statistical issues such as estimation and uncertainty of model parameters. Although written for use with human DNA, the principles can be applied to non-human genetics for animal pedigrees and/or analysis of plants for agriculture purposes. The book contains necessary tools to evaluate any type of forensic case where kinship is an issue. This volume focuses on the core material and omits most general background material on probability, statistics and forensic genetics Each chapter includes exercises with available solutions The web page familias.name contains supporting material
|Author||: Alain Cadic|
|Release Date||: 2000|
|Pages||: 356 pages|