Concurrent and Accurate Short Read Mapping on Multicore Platforms

In this paper we introduce a novel parallel work-flow-based aligner for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, named HPG Aligner W1, leverages the speed of the BurrowsWheeler Transform to map a large number of RNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm to deal with conflictive reads. The aligner is complemented with a careful strategy to detect splice junctions based on the division of RNA reads into small segments (or seeds), which are then mapped onto a number of candidate alignment locations, providing useful information for the successful alignment of the complete reads. Experimental results on a platform with AMD multicore technology report the parallel performance of HPG Aligner W, on RNA reads of 100–400 nucleotides, which excels in execution time/sensitivity to state-of-the-art aligners such as TopHat 2+Bowtie 2 and MapSplice, and compares favorably to STAR.