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Statistical Genetics Of Quantitative Traits

Author: Rongling Wu
Publisher: Springer Science & Business Media
ISBN: 038768154X
Size: 47.15 MB
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This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.

The Fundamentals Of Modern Statistical Genetics

Author: Nan M. Laird
Publisher: Springer Science & Business Media
ISBN: 9781441973382
Size: 55.33 MB
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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.

Applied Statistical Genetics With R

Author: Andrea S. Foulkes
Publisher: Springer Science & Business Media
ISBN: 038789554X
Size: 32.19 MB
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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.

Likelihood Bayesian And Mcmc Methods In Quantitative Genetics

Author: Daniel Sorensen
Publisher: Springer Science & Business Media
ISBN: 0387954406
Size: 34.42 MB
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This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style and contain much more detail than necessary. Here, an effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument.

Mathematical And Statistical Methods For Genetic Analysis

Author: Kenneth Lange
Publisher: Springer Science & Business Media
ISBN: 9780387953892
Size: 76.91 MB
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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.

Handbook Of Statistical Genetics

Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 9780470997628
Size: 39.12 MB
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The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.

A Guide To Qtl Mapping With R Qtl

Author: Karl W. Broman
Publisher: Springer Science & Business Media
ISBN: 0387921257
Size: 69.76 MB
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Comprehensive discussion of QTL mapping concepts and theory Detailed instructions on the use of the R/qtl software, the most featured and flexible software for QTL mapping Two case studies illustrate QTL analysis in its entirety

Analyzing Ecological Data

Author: Alain Zuur
Publisher: Springer Science & Business Media
ISBN: 0387459723
Size: 69.10 MB
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This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.

Statistical Genomics

Author: Ben Hui Liu
Publisher: CRC Press
ISBN: 1351414526
Size: 39.61 MB
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Genomics, the mapping of the entire genetic complement of an organism, is the new frontier in biology. This handbook on the statistical issues of genomics covers current methods and the tried-and-true classical approaches.

Statistics In Human Genetics

Author: Pak Sham
Publisher: Oxford University Press
ISBN: 9780340662410
Size: 73.36 MB
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In human genetic research sophisticated statistical methods are increasingly being used to analyse results. Until now there has been no book to introduce and explain these methods. The methods are based on both biology and statistics and are likely to contribute to major scientific and medical advances in the next century. Topics include the estimation of allele frequencies, the testing for Hardy-Weinberg equilibrium, classical and complex segregation analysis, linkage analysis for Mendelian and complex diseases and quantitative traits, the detection of allelic associations, the estimation of heritability for multifactorial traits and path analysis. An understanding of elementary statistical concepts is assumed, but the objectives, principles and limitations of the methods are discussed in detail.