Robust Parametric and Semi-Parametric Spot Fitting for Spot Array Images

Proceedings of the Twentieth International Conference on Machine Learning, 2000

Volume

Proceedings of the Twentieth International Conference on Machine Learning, 2000

Contents

In this paper we address the problem of reliably fitting parametric and semi-parametric models to spots in high density spot array images obtained in gene expression experiments. The goal is to measure the amount of label bound to an array element. A lot of spots can be modelled accurately by a Gaussian shape. In order to deal with highly overlapping spots we use robust M- estimators. When the parametric method fails (which can be detected automatically) we use a novel, robust semi-parametric method which can handle spots of different shapes accurately. The introduced techniques are evaluated experimentally.