|Title||Concurrent and Accurate Short Read Mapping on Multicore Processors.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Martinez, H, Tárraga, J, Medina, I, Barrachina, S, Castillo, M, Dopazo, J, Quintana-Orti, ES|
|Journal||IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM|
|Date Published||2015 Sep-Oct|
|Keywords||HPC; NGS; short real mapping|
We introduce a parallel aligner with a work-flow organization for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, [Formula: see text] ([Formula: see text] is an open-source application. The software is available at http://www.opencb.org, exploits a suffix array to rapidly map a large fraction of the RNA fragments (reads), as well as leverages the accuracy of the Smith-Waterman algorithm to deal with conflictive reads. The aligner is enhanced with a careful strategy to detect splice junctions based on an adaptive division of RNA reads into small segments (or seeds), which are then mapped onto a number of candidate alignment locations, providing crucial information for the successful alignment of the complete reads. The experimental results on a platform with Intel multicore technology report the parallel performance of [Formula: see text], 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, MapSplice, and STAR.