Abstract
Motivation: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.
Original language | English |
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Pages (from-to) | 2821-2828 |
Number of pages | 8 |
Journal | Bioinformatics |
Volume | 20 |
Issue number | 16 |
DOIs | |
Publication status | Published - 01 Nov 2004 |
ASJC Scopus subject areas
- Clinical Biochemistry
- Computational Theory and Mathematics
- Computer Science Applications