April 10th, 10am-11am [HMB13.356] - Gene Mapping and Marker Clustering Using Shannon's Mutual Information

This seccond entry in the Bioinformatics journal club new series will be presented by Brad Broom.

Here's the abstract to spike your interest:

January-March 2006 (Vol. 3, No. 1) pp. 47-56
Gene Mapping and Marker Clustering Using Shannon's Mutual Information
Zaher Dawy
Bernhard Goebel
Joachim Hagenauer
Christophe Andreoli
Thomas Meitinger
Jakob C. Mueller

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.9

ABSTRACT

Finding the causal genetic regions underlying complex traits is one of the main aims in human genetics. In the context of complex diseases, which are believed to be controlled by multiple contributing loci of largely unknown effect and position, it is especially important to develop general yet sensitive methods for gene mapping. We discuss the use of Shannon's information theory for population-based gene mapping of discrete and quantitative traits and for marker clustering. Various measures of mutual information were employed in order to develop a comprehensive framework for gene mapping analyses. An algorithm aimed at finding so-called relevance chains of causal markers is proposed. Moreover, entropy measures are used in conjunction with multidimensional scaling to visualize clusters of genetic markers. The relevance chain algorithm successfully detected the two causal regions in a simulated scenario. The approach has also been applied to a published clinical study on autoimmune (Graves') disease. Results were consistent with those of standard statistical methods, but identified an additional locus of interest in the promotor region of the associated gene CTLA4. The developed software is freely available at http://www.lnt.ei.tum.de/download/InfoGeneMap/.


Next meeting is April 17TH. The paper is not set yet so send your suggestions.