Towards the Development of Tandem Repeat Analyzer for Genome Sequence Data

Abstract

A Tandem repeat in DNA is two or more contiguous approximate copies of a pattern of nucleotides. Tandem repeats have been shown to cause human diseases, may play a variety of regulatory and evolutionary roles and are important laboratory and analytical tools. Extensive knowledge about pattern size, mutational history etc for tandem repeats has been limited by the inability to easily detect them in genome sequence data. In this paper, we present an algorithm for finding tandem repeats which works without the need to specify either the pattern or pattern size. We model tandem repeats by percent identity and frequency of indels between adjacent pattern copies and use statistics based recognition criteria. Detection criteria are based on a stochastic model of tandem repeats specified by percent identity and frequency of insertions and deletions rather than some minimal alignment score. Finally, the program aligns repeat copies against a consensus sequence, revealing patterns of common mutations. These patterns yield insight into the history of duplications that produce the tandem repeats thus providing a potentially valuable tool for research.