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RazerS 3: Faster, fully sensitive read mapping

Authors: David Weese; Manuel Holtgrewe; Knut Reinert;

RazerS 3: Faster, fully sensitive read mapping

Abstract

Abstract Motivation: During the past years, next-generation sequencing has become a key technology for many applications in the biomedical sciences. Throughput continues to increase and new protocols provide longer reads than currently available. In almost all applications, read mapping is a first step. Hence, it is crucial to have algorithms and implementations that perform fast, with high sensitivity, and are able to deal with long reads and a large absolute number of insertions and deletions. Results: RazerS is a read mapping program with adjustable sensitivity based on counting q-grams. In this work, we propose the successor RazerS 3, which now supports shared-memory parallelism, an additional seed-based filter with adjustable sensitivity, a much faster, banded version of the Myers’ bit-vector algorithm for verification, memory-saving measures and support for the SAM output format. This leads to a much improved performance for mapping reads, in particular, long reads with many errors. We extensively compare RazerS 3 with other popular read mappers and show that its results are often superior to them in terms of sensitivity while exhibiting practical and often competitive run times. In addition, RazerS 3 works without a pre-computed index. Availability and Implementation: Source code and binaries are freely available for download at http://www.seqan.de/projects/razers. RazerS 3 is implemented in C++ and OpenMP under a GPL license using the SeqAn library and supports Linux, Mac OS X and Windows. Contact: david.weese@fu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online.

Related Organizations
Keywords

Chromosome Mapping, High-Throughput Nucleotide Sequencing, Algorithms

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
125
Top 1%
Top 1%
Top 10%
gold