  We present Masai, a read mapper representing the state of the art in terms of
speed and sensitivity. Our tool is an order of magnitude faster than RazerS 3
and mrFAST, 2--3 times faster and more accurate than Bowtie 2 and BWA. The
novelties of our read mapper are filtration with approximate seeds and a method
for multiple backtracking. Approximate seeds, compared to exact seeds, increase
filtration specificity while preserving sensitivity. Multiple backtracking
amortizes the cost of searching a large set of seeds by taking advantage of the
repetitiveness of next-generation sequencing data. Combined together, these two
methods significantly speed up approximate search on genomic datasets. Masai is
implemented in C++ using the SeqAn library. The source code is distributed
under the BSD license and binaries for Linux, Mac OS X and Windows can be
freely downloaded from http://www.seqan.de/projects/masai.
