10% off all books and free delivery over £50
Buy from our bookstore and 25% of the cover price will be given to a school of your choice to buy more books. *15% of eBooks.

Meta-Analysis and Combining Information in Genetics and Genomics

View All Editions (1)

The selected edition of this book is not available to buy right now.
Add To Wishlist
Write A Review

About

Meta-Analysis and Combining Information in Genetics and Genomics Synopsis

Novel Techniques for Analyzing and Combining Data from Modern Biological Studies
Broadens the Traditional Definition of Meta-Analysis

With the diversity of data and meta-data now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Covering an extensive range of quantitative information combination methods, Meta-analysis and Combining Information in Genetics and Genomics looks at how to analyze multiple studies from a broad perspective.

After presenting the basic ideas and tools of meta-analysis, the book addresses the combination of similar data types: genotype data from genome-wide linkage scans and data derived from microarray gene expression experiments. The expert contributors show how some data combination problems can arise even within the same basic framework and offer solutions to these problems. They also discuss the combined analysis of different data types, giving readers an opportunity to see data combination approaches in action across a wide variety of genome-scale investigations.

As heterogeneous data sets become more common, biological understanding will be significantly aided by jointly analyzing such data using fundamentally sound statistical methodology. This book provides many novel techniques for analyzing data from modern biological studies that involve multiple data sets, either of the same type or multiple data sources.

About This Edition

ISBN: 9781584885221
Publication date:
Author: Rudy Guerra, Darlene Renee Goldstein
Publisher: Chapman & Hall/CRC an imprint of CRC Press
Format: Hardback
Pagination: 335 pages
Series: Chapman & Hall/CRC Mathematical and Computational Biology Series
Genres: Agricultural science
Genetics (non-medical)
Probability and statistics
Forestry and silviculture