A Semiparametric Regression Model For Oligonucleotide Arrays

Abstract

A semiparametric model incorporating the spline smoothing technique is proposed to study oligonucleotide gene expression data. No specific parametric functional form is assumed for mismatch probe intensities, which allows much more flexibility in the fitted model. The new approach improves the model fitting, hence the estimation of expression indexes. The method is applied to a data set of 18 HuGeneFL arrays.