Methods and approaches in the analysis of gene expression data

The application of high-density DNA array technology to monitor gene transc ription has been responsible for a real paradigm shift in biology. The majo rity of research groups now have the ability to measure the expression of a significant proportion of the human genome in a single experiment, resulti ng in an unprecedented volume of data being made available to the scientifi c community, As a consequence of this, the storage, analysis and interpreta tion of this information present a major challenge. In the field of immunol ogy the analysis of gene expression profiles has opened new areas of invest igation. The study of cellular responses has revealed that cells respond to an activation signal with waves of co-ordinated gene expression profiles a nd that the components of these responses are the key to understanding the specific mechanisms which lead to phenotypic differentiation. The discovery of 'cell type specific' gene expression signatures have also helped the in terpretation of the mechanisms leading to disease progression, Here we revi ew the principles behind the most commonly used data analysis methods and d iscuss the approaches that have been employed in immunological research. (C ) 2001 Elsevier Science B.V. All rights reserved.