Out-licensing

Cluster Analysis of Gene Expression Dynamics: A Novel Bioinformatics Tool for Microarray Data

Children's Hospital investigators have developed a new programme called CAGED (Cluster Analysis of Gene Expression Dynamics) that implements a new Bayesian statistical model for analysing repeated gene expression measurements from the same patient or cell line. Traditional clustering methods such as correlation used for analysis of microarray data are unable to handle such time series data as the values are not independent. CAGED has been specifically designed to handle data collected over a period of time. CAGED 1.0 runs on a Microsoft Windows 9x/NT/ME/2000/XP platform with a recommended 1 GB of RAM and 20 MB of hard disk space.

The method represents gene-expression dynamics as autoregressive equations and uses an agglomerative procedure to search for the most probable set of clusters given the available data. The main contributions of this approach are the ability to take into account the dynamic nature of gene expression time series during clustering and a principled way to identify the number of distinct clusters. As the number of possible clustering models grows exponentially with the number of observed time series, we have devised a distance-based heuristic search procedure able to render the search process feasible. In this way, the method retains the important visualization capability of traditional distance-based clustering and acquires an independent, principled measure to decide when two series are different enough to belong to different clusters. The reliance of this method on an explicit statistical representation of gene expression dynamics makes it possible to use standard statistical techniques to assess the goodness of fit of the resulting model and validate the underlying assumptions. A set of gene-expression time series, collected to study the response of human fibroblasts to serum, is used to identify the properties of the method.

Conclusion

A Bayesian method for model-based clustering of gene expression dynamics has been developed.

Relevance/Opportunity

CAGED can be viewed at http://genomethods.org/caged/. Please enquire regarding licensing partnerships quoting reference no. CMCC 1068.

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