MOTIVATION: Complete genomic sequences will become available in the future. New methods to deal with very large sequences (sizes beyond 100 kb) efficiently are required. One of the main aims of such work is to increase our understanding of genome organization and evolution. This requires studies of the locations of regions of similarity. RESULTS: We present here a new tool, ASSIRC ('Accelerated Search for SImilarity Regions in Chromosomes'), for finding regions of similarity in genomic sequences. The method involves three steps: (i) identification of short exact chains of fixed size, called 'seeds', common to both sequences, using hashing functions; (ii) extension of these seeds into putative regions of similarity by a 'random walk' procedure; (iii) final selection of regions of similarity by assessing alignments of the putative sequences. We used simulations to estimate the proportion of regions of similarity not detected for particular region sizes, base identity proportions and seed sizes. This approach can be tailored to the user's specifications. We looked for regions of similarity between two yeast chromosomes (V and IX). The efficiency of the approach was compared to those of conventional programs BLAST and FASTA, by assessing CPU time required and the regions of similarity found for the same data set. AVAILABILITY: Source programs are freely available at the following address: ftp://ftp.biologie.ens. fr/pub/molbio/assirc.tar.gz CONTACT: vincens@biologie.ens.fr, hazout@urbb.jussieu.fr
MOTIVATION: Complete genomic sequences will become available in the future. New methods to deal with very large sequences (sizes beyond 100 kb) efficiently are required. One of the main aims of such work is to increase our understanding of genome organization and evolution. This requires studies of the locations of regions of similarity. RESULTS: We present here a new tool, ASSIRC ('Accelerated Search for SImilarity Regions in Chromosomes'), for finding regions of similarity in genomic sequences. The method involves three steps: (i) identification of short exact chains of fixed size, called 'seeds', common to both sequences, using hashing functions; (ii) extension of these seeds into putative regions of similarity by a 'random walk' procedure; (iii) final selection of regions of similarity by assessing alignments of the putative sequences. We used simulations to estimate the proportion of regions of similarity not detected for particular region sizes, base identity proportions and seed sizes. This approach can be tailored to the user's specifications. We looked for regions of similarity between two yeast chromosomes (V and IX). The efficiency of the approach was compared to those of conventional programs BLAST and FASTA, by assessing CPU time required and the regions of similarity found for the same data set. AVAILABILITY: Source programs are freely available at the following address: ftp://ftp.biologie.ens. fr/pub/molbio/assirc.tar.gz CONTACT: vincens@biologie.ens.fr, hazout@urbb.jussieu.fr