RNAz 2.0: Improved Noncoding RNA Detection

Andreas R. Gruber1,2, Sven Findeiß1, Stefan Washietl2,3, Ivo L. Hofacker2, Peter F. Stadler1,2

1Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany; 2 Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria.; 3European Molecular Biology Laboratory - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK

Pacific Symposium on Biocomputing 15:69-79(2010)


RNAz is a widely used software package for de novo detection of structured noncoding RNAs in comparative genomics data. Four years of experience have not only demonstrated the applicability of the approach, but also helped us to identify limitations of the current implementation. RNAz 2.0 provides significant improvements in two respects: (1) The accuracy is increased by the systematic use of dinucleotide models. (2) Technical limitations of the previous version, such as the inability to handle alignments with more than six sequences, are overcome by increased training data and the usage of an entropy measure to represent sequence similarities. RNAz 2.0 shows a significantly lower false discovery rate on a dinucleotide background model than the previous version. Separate models for structural alignments provide an additional way to increase the predictive power. RNAz is open source software and can be obtained free of charge at: http://www.tbi.univie.ac.at/~wash/RNAz/

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