Overview
- covers microarray data analysis, which is absent in both competing books in addition to QTL mapping
- introduces Bayesian method, which was not available in both competing books
- uses more rigorous mathematical approaches to derive the statistical methods
- Includes supplementary material: sn.pub/extras
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Table of contents (25 chapters)
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Front Matter
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Genetic Linkage Map
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Front Matter
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Analysis of Quantitative Traits
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Front Matter
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Microarray Data Analysis
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Front Matter
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Keywords
About this book
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.
Reviews
From the reviews:
“The book was compiled from a collection of lecture notes for a statistical genomics course offered to University California Riverside graduate students by the author. It can be used as a textbook for graduate students in statistical genomics, but also by researchers as a reference book. … For advanced readers of this very modern book in a new field of biometrics, they can choose to read any particular chapters as they desire in this multidisciplinary area.” (T. Postelnicu, zbMATH, Vol. 1276, 2014)Authors and Affiliations
About the author
University of California, Department of Botany and Plant Sciences, Riverside, CA, USA
Bibliographic Information
Book Title: Principles of Statistical Genomics
Authors: Shizhong Xu
DOI: https://doi.org/10.1007/978-0-387-70807-2
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media, LLC 2013
Hardcover ISBN: 978-0-387-70806-5Published: 10 September 2012
Softcover ISBN: 978-1-4899-9404-2Published: 15 October 2014
eBook ISBN: 978-0-387-70807-2Published: 13 September 2012
Edition Number: 1
Number of Pages: XVI, 428
Topics: Plant Genetics and Genomics, Animal Genetics and Genomics