Look4TRs: A de-novo tool for detecting simple tandem repeats using self-supervised hidden Markov models

Abstract

ABSTRACTSimple tandem repeats, microsatellites in particular, have regulatory functions, links to several diseases, and applications in biotechnology. Sequences of thousands of species will be available soon. There is immediate need for an accurate tool for detecting microsatellites in the new genomes. The current available tools have limitations. As a remedy, we proposed Look4TRs, which is the first application of self-supervised hidden Markov models to discovering microsatellites. It adapts itself to the input genomes, balancing high sensitivity and low false positive rate. It auto-calibrates itself, freeing the user from adjusting the parameters manually, leading to consistent results across different studies. We evaluated Look4TRs on eight genomes. Based on F-measure, which combines sensitivity and false positive rate, Look4TRs outperformed TRF and MISA — the most widely-used tools — by 106% and 82%. Look4TRs outperformed the second best tool, MsDetector or Tantan, by 11%. Look4TRs represents technical advances in the annotation of microsatellites.