Biomathematics & Statistics Scotland
The first stage in the analysis of microarray data is estimation from laser scans of the level of expression of each gene. Typically, data are only used from a single scan, although, if multiple scans are available, sampling error can be reduced by combining them: a functional regression problem. Maximum likelihood estimation fails, but many alternative estimators exist, one of which is to maximise the likelihood of a Gaussian structural regression model. We have found by simulation that, surprisingly, this estimator is efficient for our particular application, even though the distribution of gene expressions is severely skewed and hence far from Gaussian.
Measured responses from laser scans 2, 3 and 4 plotted against those from laser scan for each gene in a murine macrophage experiment (Division of Pathway Medicine, University of Edinburgh).
Further details from: Chris Glasbey
