Summary: Studies on gene clusters proved to be an excellent source of information to understand genomes evolution and identifying specific metabolic pathways or gene families. Improvements in sequencing methods have resulted in a large increase of sequenced genomes for which cluster annotation could be performed and standardized. Currently available programs are developed to search for specific cluster types and none of them is suitable for a broad range of user-based choices. We have developed ClusterScan which allows identifying clusters of any kind of feature simply based on their genomic coordinates and user-defined categorical annotations.
Availability and implementation: The tool is written in Python, distributed under the GNU General Public License (GPL) and available on Github at http://bit.ly/ClusterScan or as Docker image at sangeslab/clusterscan: latest. It is supported through a mailing-list on http://bit.ly/ClusterScanSupport.
Supplementary information: Supplementary data are available at Bioinformatics online.