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BMCBI
2010

Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes

11 years 11 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one searches for differentially expressed genes, the small number of samples gives rise to an inaccurate estimation of the experimental noise. This, in turn, leads to loss of statistical power. Results: We show that the measurement noise of genes with similar expression levels (intensity) is identically and independently distributed, and that this (intensity dependent) distribution is approximately normal. Our method can be easily adapted and used to test whether these statement hold for data from any particular microarray experiment. We propose a method that provides an accurate estimation of the intensity-dependent variance of the noise distribution, and demonstrate that using this estimation we can detect differential expression with much better statistical power than that of standard t-test, and can compare t...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Amit Zeisel, Amnon Amir, Wolfgang J. Köstler, Eytan Domany
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