MOTIVATION: 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. AVAILABILITY: The implementation of RBR is available under the terms of the GPL from http://www.ii.uib.no/~ketil/bioinformatics CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: EST sequences constitute an abundant, yet error prone resource for computational biology. Expressed sequences are important in gene discovery and identification, and they are also crucial for the discovery and classification of alternative splicing. An important challenge when processing EST sequences is the reconstruction of mRNA by assembling EST clusters into consensus sequences. RESULTS: In contrast to the more established assembly tools, we propose an algorithm that constructs a graph over sequence fragments of fixed size, and produces consensus sequences as traversals of this graph. We provide a tool implementing this algorithm, and perform an experiment where the consensus sequences produced by our implementation, as well as by currently available tools, are compared to mRNA. The results show that our proposed algorithm in a majority of the cases produces consensus of higher quality than the established sequence assemblers and at a competitive speed. AVAILABILITY: The source code for the implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bioinformatics/ CONTACT: [email protected].

MOTIVATION: Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data. RESULTS: A new, fast EST clustering algorithm is presented. Sub-quadratic time complexity is achieved by using an algorithm based on suffix arrays. A prototype implementation has been developed and run on a benchmark data set. The produced clusterings are validated by comparing them to clusterings produced by other methods, and the results are quite promising. AVAILABILITY: The source code for the prototype implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bio/.

Abstract Summary: Shufflet is a program and a web-application that generates fast random shufflings of sequences (DNA, protein or others), conserving the exact k-let counts for a given k. The sequences are sampled uniformly from all the valid permutations. Availability: As a web application: http://www.genetique.uvsq.fr/eivind/shufflet.html. Source code is available on request for academic use. Contact: [email protected]

MOTIVATION: The search for repeated patterns in DNA and protein sequences is important in sequence analysis. The rapid increase in available sequences, in particular from large-scale genome sequencing projects, makes it relevant to develop sensitive automatic methods for the identification of repeats. RESULTS: A new method for finding periodic patterns in biological sequences is presented. The method is based on evolutionary distance and 'phase shifts' corresponding to insertions and deletions. A given sequence is aligned to itself in a certain sense, trying to minimize a distance to periodicity. Relationships between different such periodicity measures are discussed. An iterative algorithm is used, and the running time is nearly proportional to the sequence length. The alignment produces a periodic consensus pattern. A 'phase score' is used to indicate a statistical significance of the periodicity. Three examples using both DNA and protein sequences illustrate how the method can be used to find patterns. AVAILABILITY: On request from the authors. CONTACT: evindc@mat nu.no; [email protected]