RazerS
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Application data |
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| Created by | David Weese, Anne-Katrin Emde, Tobias Rausch, Andreas Döring, and Knut Reinert |
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| Biological application domain(s) | Mapping |
| Principal bioinformatics method(s) | Local sequence alignment, Read mapping |
| Technology | Sanger, Illumina, 454 |
| Created at | Free University of Berlin |
| Maintained? | Yes |
| Input format(s) | FASTA, FASTQ |
| Output format(s) | SAM, AMOS, GFF, Eland |
| Software features | Gapped alignment, paired-end mapping |
| Programming language(s) | C++ |
| Software libraries | SeqAn |
| Licence | GPLv3 |
| Operating system(s) | UNIX, Mac OS X, Windows |
| Contact: | weese@inf.fu-berlin.de |
Summary: RazerS allows the user to align sequencing reads of arbitrary length using either the Hamming distance or the edit distance. The tool can work either lossless or with a user-defined loss rate at higher speeds.
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Second-generation sequencing technologies deliver DNA sequence data at unprecedented high throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. Due to the large amounts of data, efficient algorithms and implementations are crucial for this task. We present an efficient read mapping tool called RazerS. It allows the user to align sequencing reads of arbitrary length using either the Hamming distance or the edit distance. Our tool can work either lossless or with a user-defined loss rate at higher speeds. Given the loss rate, we present an approach that guarantees not to lose more reads than specified. This enables the user to adapt to the problem at hand and provides a seamless tradeoff between sensitivity and running time.
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