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BMCBI
2004

Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an

9 years 1 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge requires careful examination of the performance of a range of statistical models, as well as empirical examination of the effect of replication on the power to resolve these differences. Results: New models are derived and software is developed for the analysis of microarray ratio data. These models incorporate multiplicative small error terms, and error standard deviations that are proportional to expression level. The fastest and most powerful method incorporates additive small error terms and error standard deviations proportional to expression level. Data from four studies are profiled for the degree to which they reveal statistically significant differences in gene expression. The gene expression level at which there is an empirical 50% probability of a significant call is presented as a summary statistic...
Jeffrey P. Townsend
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where BMCBI
Authors Jeffrey P. Townsend
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