For many years the attempts to identify functional elements in genomic sequences through motif over- representation have been problematic, as every procedure to isolate such motifs resulted in a very large number of candidates with highly significant p-values. In this paper we postulate that most of these elements originate in ancient transpositional activity, with copies becoming so broken over time that they cannot be recognized as such any more. We have written a software tool which efficiently locates possible ancient repeats and, while the nature of much of our findings in real genomic sequences have yet to be confirmed by further biological analysis, our test results on well understood data sets have been encouraging.

Summary form only given. The sequencing of the human genome would not have been possible without software - and, because of the specific nature of this effort, very little of it was previously available. We provide an overview of the programs developed for the human genome project, some of which have not been published before. The sequencing was officially completed in 2003, but its results (in combination with other obtained genomes) enabled the analysis on a grand scale. That mandated even more complex programming work. We conclude with an outline of several research directions which, in this author's opinion, become increasingly important.

MOTIVATION: When studying multiple alignments of genomic sequences one frequently aims to locate and count regions which satisfy a set of constraints. These regions may be putatively functional, but researchers may also be interested in quantifying the frequency of occurrences of certain patterns. RESULTS: We have developed a program that applies simple formulas and pattern specifications to multiple alignments, reporting the positions and counts of conforming regions. As an example, we have navigated a 15-species alignment of the CAV2-CAV1 region and outlined some findings regarding PPARgamma binding sites. AVAILABILITY: Our software and the accompanying documentation can be obtained at no charge by contacting the authors. It can also be accessed at http://ranger.uta.edu/~nick/compgen

Abstract Motivation: During the process of high-throughput genome sequencing there are opportunities for mixups of reagents and data associated with particular projects. The sequencing templates or sequence data generated for an assembly may become contaminated with reagents or sequences from another project, resulting in poorer quality and inaccurate assemblies. Results: We have developed a system to assess sequence assemblies and monitor for laboratory mixups. We describe several methods for testing the consistency of assemblies and resolving mixed ones. We use statistical tests to evaluate the distribution of sequencing reads from different plates into contigs, and a graph-based approach to resolve situations where data has been inappropriately combined. While these methods have been designed for use in a high-throughput DNA sequencing environment processing thousands of clones, they can be applied in any situation where distinct sequencing projects are performed at redundant coverage. Availability: Our software is available for downloading from: ftp-genome.wi.mit.edu/distribution/mixups_detection Contact: [email protected] * To whom correspondence should be addressed.