Parallelization of BLAST with MapReduce for Long Sequence Alignment

Abstract

Sequence alignment is of great importance in biology research. BLAST is a sequence alignment tool used extensively by researchers. However the continuously increasing amount of sequence data to be processed presents many challenges to it. This paper gives a simple and effective approach to parallelizing BLAST using the MapReduce technique. The MapReduce-BLAST shows very good performance and scales nearly linearly to the database size and query length. This results from both the power of MapReduce and the inherent parallel characteristics of the BLAST algorithm. Sequence alignment algorithms based on techniques similar with BLAST's seed-and-extend approach are very suitable for being parallelized with MapReduce.