Summaries of Affymetrix GeneChip probe level data

TLDR

High‑density oligonucleotide arrays, especially Affymetrix GeneChip platforms, are widely used in biomedical research, with each gene represented by 11–20 probe pairs. The study aims to develop methods for summarizing probe‑level data to generate reliable expression measures. The authors used two large spike‑in studies and a dilution experiment to develop tools that evaluate the effectiveness of expression measures. They demonstrated that probe‑level summaries based on empirically motivated statistical models significantly improve the default Affymetrix expression measure, especially in detecting differentially expressed genes.

Abstract

High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11–20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike‐in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated.