MOTIVATION: New generation sequencing technologies producing increasingly 
complex datasets demand new efficient and specialized sequence analysis 
algorithms. Often, it is only the 'novel' sequences in a complex dataset that 
are of interest and the superfluous sequences need to be removed.
RESULTS: A novel algorithm, fast and accurate classification of sequences 
(FACSs), is introduced that can accurately and rapidly classify sequences as 
belonging or not belonging to a reference sequence. FACS was first optimized and 
validated using a synthetic metagenome dataset. An experimental metagenome 
dataset was then used to show that FACS achieves comparable accuracy as BLAT and 
SSAHA2 but is at least 21 times faster in classifying sequences.
AVAILABILITY: Source code for FACS, Bloom filters and MetaSim dataset used is 
available at http://facs.biotech.kth.se. The Bloom::Faster 1.6 Perl module can 
be downloaded from CPAN at http://search.cpan.org/ approximately 
palvaro/Bloom-Faster-1.6/
CONTACTS: henrik.stranneheim@biotech.kth.se; joakiml@biotech.kth.se
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics 
online.