INTRODUCTION

The image of the microarray generated by the scanner (Section 1.3) is the raw data of your experiment. Computer algorithms, known as feature extraction software, convert the image into the numerical information that quantifies gene expression; this is the first step of data analysis. The image processing involved in feature extraction has a major impact on the quality of your data and the interpretation you can place on it.

In Chapter 1 we discussed three technologies by which microarrays are manufactured: in-situ synthesis with the Affymetrix platform, inkjet in-situ synthesised arrays (Rosetta, Agilent and Oxford Gene Technology) and pin-spotted microarrays. This chapter focusses on pin-spotted arrays. Affymetrix has integrated its image processing algorithms into the Gene Chip experimental process and there are no decisions for the end-user to make. Inkjet arrays are of much higher quality than pin-spotted arrays and do not suffer from many of the image-processing difficulties of spotted arrays; also, Agilent provides image-processing software tailor-made for their platform, so there are no decisions for the end-user either.

Pin-spotted arrays, on the other hand, provide the user with a wide range of choices of how to process the image. These choices have an impact on the data, and so this chapter describes the fundamentals of these computational methods to give a better understanding as to how they impact the data.

FEATURE EXTRACTION

The first step in the computational analysis of microarray data is to convert the digital TIFF images of hybridisation intensity generated by the scanner into numerical measures of the hybridisation intensity of each channel on each feature. This process is known as feature extraction.