A Parallel Evolutionary Method for Physical Mapping of Chromosomes

Reconstructing a physical map of a chromosome from a genomic library presents a central com putational problem in genetics Physical map reconstruction in the presence of errors is a prob lem of high computational complexity A parallel evolutionary method for a maximum likelihood estimation based approach to physical map reconstruction is presented The estimation procedure entails gradient descent search for determining the optimal spacings between probes for a given probe ordering The optimal probe ordering is determined using an evolutionary algorithm A two tier parallelization strategy is proposed wherein the gradient descent search is parallelized at the lower level and the evolutionary algorithm is simultaneously parallelized at the higher level Implementa tion and experimental results on a network of shared memory symmetric multiprocessors SMPs are presented The evolutionary algorithm is seen to result in physical maps with fewer contig breaks when compared to simulated Monte Carlo algorithms such as simulated annealing and the large step Markov chain algorithm