Use of Bioinformatics in Arrays

Previous chapters have discussed in detail how to prepare, print and hybridize DNA arrays on various surfaces. Once hybridization is completed, the next step is to scan in the glass, gel, or plastic slides with a specialized scanner to obtain digital images of the results of the experiment. The DNA expression levels are then quantified with the help of image-analysis software. After the image processing and analysis step is completed, we end up with a large number of quantified gene expression values. The data typically represent hundreds or thousands, in certain cases tens of thousands, of gene expressions across multiple experiments. To make sense of this much information requires the use various of visualization and statistical analysis techniques. One of the most typical microarray data analysis goal is to find statistically significantly up- or downregulated genes; in other words outliers or “interestingly” behaving genes in the data. Other possible goals could be to find functional groupings of genes by discovering similarity or dissimilarity among gene-expression profiles, or predicting the biochemical and physiological pathways of previously uncharacterized genes.