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Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self–self hybridizations

Paper ID Volume ID Publish Year Pages File Format Full-Text
15452 1414 2007 8 PDF Available
Title
Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self–self hybridizations
Abstract

Our ability to detect differentially expressed genes in a microarray experiment can be hampered when the number of biological samples of interest is limited. In this situation, we propose the use of information from self–self hybridizations to acuminate our inference of differential expression. A unified modelling strategy is developed to allow better estimation of the error variance. This principle is similar to the use of a pooled variance estimate in the two-sample t-test. The results from real dataset examples suggest that we can detect more genes that are differentially expressed in the combined models. Our simulation study provides evidence that this method increases sensitivity compared to using the information from comparative hybridizations alone, given the same control for false discovery rate. The largest increase in sensitivity occurs when the amount of information in the comparative hybridization is limited.

Keywords
Linear models; Self–self hybridizations; Differentially expressed; Gene expressions; Microarray
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Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self–self hybridizations
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Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 31, Issue 3, June 2007, Pages 178–185
Authors
, , , , , , , , , , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us