Dinucleotide controlled null models for comparative RNA gene prediction

Background: Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results: We present a program called SISSId that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Tanja Gesell, Stefan Washietl
• Keywords: BMCBI 2008, Dinucleotide Content, Multiple Alignments, Rna Structure