@article {10, title = {Concurrent and Accurate Short Read Mapping on Multicore Processors.}, journal = {IEEE/ACM Trans Comput Biol Bioinform}, volume = {12}, year = {2015}, month = {2015 Sep-Oct}, pages = {995-1007}, abstract = {

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, HPG Aligner SA (HPG Aligner SA 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 HPG Aligner SA, 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.

}, issn = {1557-9964}, doi = {10.1109/TCBB.2015.2392077}, author = {Mart{\'\i}nez, H{\'e}ctor and Tarraga, Joaquin and Medina, Ignacio and Barrachina, Sergio and Castillo, Maribel and Dopazo, Joaqu{\'\i}n and Quintana-Ort{\'\i}, Enrique S} } @article {8, title = {Acceleration of short and long DNA read mapping without loss of accuracy using suffix array.}, journal = {Bioinformatics}, volume = {30}, year = {2014}, month = {2014 Dec 1}, pages = {3396-8}, abstract = {

UNLABELLED: HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20{\texttimes} for long reads) and more sensitive (over 98\% in a wide range of read lengths) than the current state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.

AVAILABILITY AND IMPLEMENTATION: https://github.com/opencb/hpg-aligner.

}, keywords = {Algorithms, Animals, DNA, Drosophila, High-Throughput Nucleotide Sequencing, Humans, Sequence Alignment, Sequence Analysis, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btu553}, author = {Tarraga, Joaquin and Arnau, Vicente and Mart{\'\i}nez, H{\'e}ctor and Moreno, Raul and Cazorla, Diego and Salavert-Torres, Jos{\'e} and Blanquer-Espert, Ignacio and Dopazo, Joaqu{\'\i}n and Medina, Ignacio} }