RBR: library-less repeat detection for ESTs.
BACKGROUND
Repeat sequences in ESTs are a source of problems, in particular for clustering. ESTs are therefore commonly masked against a library of known repeats. High quality repeat libraries are available for the widely studied organisms, but for most other organisms the lack of such libraries is likely to compromise the quality of EST analysis.


RESULTS
We present a fast, flexible and library-less method for masking repeats in EST sequences, based on match statistics within the EST collection. The method is not linked to a particular clustering algorithm. Extensive testing on datasets using different clustering methods and a genomic mapping as reference shows that this method gives results that are better than or as good as those obtained using RepeatMasker with a repeat library.


BACKGROUND
The implementation of RBR is available under the terms of the GPL from http://www.ii.uib.no/~ketil/bioinformatics


BACKGROUND
ketil.malde@bccs.uib.no


BACKGROUND
Supplementary data are available at Bioinformatics online.
Malde
Ketil
K
Computational Biology Unit, Bergen Centre for Computational Sciences, University of Bergen, Norway. ketil.malde@bccs.uib.no
Schneeberger
Korbinian
K
Coward
Eivind
E
Jonassen
Inge
I
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D016000:Cluster Analysis; D020224:Expressed Sequence Tags; D015723:Gene Library; D008969:Molecular Sequence Data; D012091:Repetitive Sequences, Nucleic Acid / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software