Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies
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Updated: Jul 20, 2026

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces
Published on: March 1, 2017
Thomas E Royce1, Joel S Rozowsky, Nicholas M Luscombe
1Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Abstract:
A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance.
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