Cutting-edge computational molecular biology research featured in Genome Research

Genome-wide association studies are an important early step in the identification of genetic markers associated with disease and disorders. A limitation of current analysis methods is that all candidate markers are considered equal in their potential to be involved in the disease, when in actuality, some markers might be more likely to play a role in disease than others. By taking into consideration preexisting information about allele association and gene function, the statistical power of association studies could be significantly improved.

In this work, University of California, Los Angeles researcher Dr. Eleazar Eskin has derived a new method, Multi-threshold Association Study Analysis, which makes use of prior knowledge about markers and gene function that has been underutilized in association studies. "This paper presents a method for incorporating this information into genetic association studies which can increase their ability to discover genes involved in disease,” describes Eskin. “As efforts such as the ENCODE project mature, which attempt to predict the function of every region of the human genome, a tremendous amount of this type of information is becoming available.”

Reference:
Eskin, E. Increasing power in association studies by using linkage disequilibrium structure and molecular function as prior information. Genome Res. doi:10.1101/gr.072785.107.

Contact:
Eleazar Eskin, Ph.D., University of California, Los Angeles, Los Angeles, CA, USA

Please direct requests for pre-print copies of the manuscripts to Peggy Calicchia, Genome Research Editorial Secretary ( ; +1-516-422-4012).

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