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.
General
| Imprint: |
Crc Press
|
| Country of origin: |
United Kingdom |
| Series: |
Chapman & Hall/CRC Computational Biology Series |
| Release date: |
June 2017 |
| First published: |
2010 |
| Authors: |
Rudy Guerra
• Darlene R. Goldstein
|
| Dimensions: |
234 x 156mm (L x W) |
| Format: |
Paperback
|
| Pages: |
360 |
| ISBN-13: |
978-1-138-11611-5 |
| Categories: |
Books >
Science & Mathematics >
Mathematics >
General
|
| LSN: |
1-138-11611-4 |
| Barcode: |
9781138116115 |
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