Modelling background intensity in Affymetrix Genechips

TL;DR

This paper introduces a physics-based model for estimating background noise in Affymetrix Genechips, combining sequence affinity and spatial correlations, outperforming purely statistical methods.

Contribution

A novel background estimation model for Genechips that integrates sequence-dependent hybridization and neighbor intensity correlations, with parameters fixed by data minimization.

Findings

Sequence parameters correlate with RNA/DNA hybridization energies.

Model agrees well with experimental background data.

Performs better than purely statistical background correction methods.

Abstract

DNA microarrays are devices that are able, in principle, to detect and quantify the presence of specific nucleic acid sequences in complex biological mixtures. The measurement consists in detecting fluorescence signals from several spots on the microarray surface onto which different probe sequences are grafted. One of the problems of the data analysis is that the signal contains a noisy background component due to non-specific binding. This paper presents a physical model for background estimation in Affymetrix Genechips. It combines two different approaches. The first is based on the sequence composition, specifically its sequence dependent hybridization affinity. The second is based on the strong correlation of intensities from locations which are the physical neighbors of a specific spot on the chip. Both effects are incorporated in a background functional which contains 24 free parameters, fixed by minimization on a training data set. In all data analyzed the sequence specific parameters, obtained by minimization, are found to strongly correlate with empirically determined stacking free energies for RNA/DNA hybridization in solution. Moreover, there is an overall agreement with experimental background data and we show that the physics-based model proposed in this paper performs on average better than purely statistical approaches for background calculations. The model thus provides an interesting alternative method for background subtraction schemes in Affymetrix Genechips.