Overview

Surveys of the levels of mRNA in cells provide a rich source of data from which inferences about both overall cell function and the function of individual gene components can be drawn. A wide variety of analytical tools are used to carry out such analysis. The first step in any analysis of microarray data is extraction of quantitative information from the images resulting from the readout of fluorescent or radioactive hybridizations (Image Analysis). A second general step in the analysis of this data is the collection of experimental data into a database that supports both further mathematical analysis and connection to the available knowledge about the structure and function of the individual genes (Database Design & Development).

Preliminary analysis of the data from experiments then proceeds in two stages. In the first stage, the data from each experiment is assessed for overall quality, and to judge the extent of difference between the experimental sample and the reference sample. Tools for normalizing the data between experimental and reference samples, and for judging the level of change required for statistical significance between experimental and reference samples are utilized. At the next level, experiments are compared against each other, allowing visualization of similarities or differences at the gene by gene level or at the experiment by experiment level. Class discovery tools that group samples on the basis of similarities in overall expression patterns are frequently utilized in this stage of analysis (Data Visualization).

The way in which particular genes' expression patterns vary across the samples can be analyzed in a variety of ways. Two general types of query ask whether the similarities of these patterns between genes suggest involvement in common processes, or whether differences in the individual gene expression patterns can be aligned with differences in the sample types (Expression Clustering). Methods of analysis that find the genes having the most differential behavior between samples can be used to try to identify the particular cellular activities that differ between classes of samples (Discriminative Gene List).