Concurrent and Accurate Short Read Mapping on Multicore Processors

IEEE/ACM Trans Comput Biol Bioinform. 2015 Sep-Oct;12(5):995-1007. doi: 10.1109/TCBB.2015.2392077.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Base Sequence
  • Chromosome Mapping / instrumentation*
  • Chromosome Mapping / methods
  • Equipment Design
  • Equipment Failure Analysis
  • High-Throughput Nucleotide Sequencing / instrumentation*
  • High-Throughput Nucleotide Sequencing / methods
  • Molecular Sequence Data
  • RNA / genetics*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Sequence Alignment / instrumentation
  • Sequence Alignment / methods
  • Sequence Analysis, RNA / instrumentation*
  • Sequence Analysis, RNA / methods
  • Signal Processing, Computer-Assisted / instrumentation*
  • Software*

Substances

  • RNA