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ABSTRACT: Background
Rapid evolutions in sequencing technology force read mappers into flexible adaptation to longer reads, changing error models, memory barriers and novel applications.Results
ALFALFA achieves a high performance in accurately mapping long single-end and paired-end reads to gigabase-scale reference genomes, while remaining competitive for mapping shorter reads. Its seed-and-extend workflow is underpinned by fast retrieval of super-maximal exact matches from an enhanced sparse suffix array, with flexible parameter tuning to balance performance, memory footprint and accuracy.Conclusions
ALFALFA is open source and available at http://alfalfa.ugent.be .
SUBMITTER: Vyverman M
PROVIDER: S-EPMC4449525 | biostudies-literature | 2015 May
REPOSITORIES: biostudies-literature