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Free keywords:
Gene Expression, Microarray, Robust Regression, Variance Stabilization
Abstract:
We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of di erential gene expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements,
and a di erence statistic 4h whose variance is approximately constant along the intensity range. The parametric form h(x) = arsinh(a + bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation.
