We present the q-group index, a novel data structure for read mapping tailored towards graphics processing units (GPUs) with a small memory footprint and efficient parallel algorithms for querying and building. On top of the q-group index we introduce PEANUT, a highly parallel GPU-based read mapper. PEANUT provides the possibility to output both the best hits or all hits of a read. Our benchmarks show that PEANUT outperforms other state-of-the-art read mappers in terms of speed while maintaining or slightly increasing precision, recall and sensitivity.

Additional Metadata
Persistent URL dx.doi.org/10.7717/peerj.606
Journal PeerJ
Grant This work was funded by the The Netherlands Organisation for Scientific Research (NWO); grant id nwo/639.072.309 - Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
Citation
Köster, J, & Rahmann, S. (2014). Massively parallel read mapping on GPUs with the q-group index and PEANUT. PeerJ, 2014(1). doi:10.7717/peerj.606