IBM Israel Research Seminars

Linkage analysis is a tool used by geneticists for mapping disease-susceptibility genes in the study of Mendelian and complex diseases. However analyses of large inbred pedigrees with extensive missing data are often beyond the capabilities of a single computer. We present a distributed system called Superlink-Online for computing multipoint LOD scores of large inbred pedigrees. It achieves high performance via efficient parallelization of the algorithms in Superlink, a state-of-the-art serial program for these tasks, and through utilization of thousands of resources residing in multiple opportunistic grid environments. Notably, the system is available online, which allows computationally intensive analyses to be performed with no need for either installation of software, or maintenance of a complicated distributed environment. The main algorithmic challenges have been to efficiently split large tasks for distributed execution in highly dynamic non-dedicated running environment, as well as to utilize resources in all the available grid environments, providing nearly interactive response time for shorter tasks while simultaneously serving massively parallel ones. The system is being extensively used by medical centers worldwide, achieving speedups of up to three orders of magnitude and allowing analyses which have not been feasible previously.

This work has been done as a part of PhD studies in the Technion under joint supervision of Prof. Assaf Schuster and Dan Geiger. It has been published in American Journal of Human Genetics and presented at High Performance Distributed Computing conference in 2006.

About the Speaker
Mark Silberstein is a PhD student at the CS department in the Technion under the joint supervision of Prof. Assaf Schuster and Dan Geiger. His main research focus has been efficient serial and parallel algorithms for inference in Bayesian networks (in the context of genetic linkage analysis), and their execution in large-scale opportunistic computing environments, aka Grids. Prior to starting his PhD, Mark worked for few years as a student in HRL.