Several methods for combining information from different studies specific to genetic and genomic areas are explained by researchers in statistics and in various biological disciplines. They consider in turn combining similar genotype data, combining similar gene expression data, and combining different data types. Among their topics are combining information across genome-wide linkage scans, heterogeneity in the meta-analysis of quantitative trait linkage studies, an approach to composite hypothesis testing built on intersection-union tests and Bayesian posterior probabilities, significance testing for small microarray experiments, combining genomic data in human studies, and a misclassification model for inferring transcriptional regulatory networks. Annotation ©2009 Book News, Inc., Portland, OR (booknews.com)
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.
