KABOOM! A new suffix array based algorithm for clustering expression data

• Published in: Bioinformatics Vol. 27; no. 24; pp. 3348 - 3355
• Main Authors: Hazelhurst, Scott, Lipták, Zsuzsanna
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 15.12.2011
• Subjects: Algorithms; Artificial Intelligence; Biological and medical sciences; Cluster Analysis; Computational Biology - economics; Computational Biology - methods; Fundamental and applied biological sciences. Psychology; Gene Expression Profiling; General aspects; Humans; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Software; Cluster analysis; Array; Automatic classification; Data; Suffix; Clustering algorithm
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btr560

Motivation: Second-generation sequencing technology has reinvigorated research using expression data, and clustering such data remains a significant challenge, with much larger datasets and with different error profiles. Algorithms that rely on all-versus-all comparison of sequences are not practical for large datasets. Results: We introduce a new filter for string similarity which has the potential to eliminate the need for all-versus-all comparison in clustering of expression data and other similar tasks. Our filter is based on multiple long exact matches between the two strings, with the additional constraint that these matches must be sufficiently far apart. We give details of its efficient implementation using modified suffix arrays. We demonstrate its efficiency by presenting our new expression clustering tool, wcd-express, which uses this heuristic. We compare it to other current tools and show that it is very competitive both with respect to quality and run time. Availability: Source code and binaries available under GPL at http://code.google.com/p/wcdest. Runs on Linux and MacOS X. Contact: scott.hazelhurst@wits.ac.za; zsuzsa@cebitec.uni-bielefeld.de Supplementary Information: Supplementary data are available at Bioinformatics online.