Authors:
- Multivariate analysis in genetic studies Powerful and flexible statistical solutions
- Fully nonparametric analysis
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (7 chapters)
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Front Matter
About this book
The purpose of this book is to illustrate a new statistical approach to test allelic association and genotype-specific effects in the genetic study of diseases. There are some parametric and non-parametric methods available for this purpose. We deal with population-based association studies, but comparisons with other methods will also be drawn, analysing the advantages and disadvantages of each one, particularly with regard to power properties with small sample sizes. In this framework we will work out some nonparametric statistical permutation tests and likelihood-based tests to perform case-control analyses to study allelic association between marker, disease-gene and environmental factors. Permutation tests, in particular, will be extended to multivariate and more complex studies, where we deal with several genes and several alleles together. Furthermore, we show simulations under different assumptions on the genetic model and analyse real data sets by simply studying one locus with the permutation test.
Authors and Affiliations
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Department of Management and, Engineering, University of Padova, Vicenza, Italy
Luigi Salmaso
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Department of Territory and, Agri-Foresta, University of Padova, Padova, Italy
Rosa Arboretti
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Department of, Management and Engineering, University of Padova, Vicenza, Italy
Livio Corain
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Assicurazioni Generali s.p.a., Generali Group, Mogliano Veneto (TV), Italy
Dario Mazzaro
About the authors
Bibliographic Information
Book Title: Permutation Testing for Isotonic Inference on Association Studies in Genetics
Authors: Luigi Salmaso, Rosa Arboretti, Livio Corain, Dario Mazzaro
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-642-20584-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Berlin Heidelberg 2011
Softcover ISBN: 978-3-642-20583-5Published: 09 July 2011
eBook ISBN: 978-3-642-20584-2Published: 09 July 2011
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: VI, 72
Number of Illustrations: 13 b/w illustrations
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Human Genetics, Biological Techniques, Biotechnology, Psychometrics, Pharmacy