PERF: an exhaustive algorithm for ultra-fast and efficient identification of microsatellites from large DNA sequences

• Published in: Bioinformatics Vol. 34; no. 6; pp. 943 - 948
• Main Authors: Avvaru, Akshay Kumar, Sowpati, Divya Tej, Mishra, Rakesh Kumar
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.03.2018
• Subjects: Algorithms; Genome, Human; Genomics - methods; Humans; Microsatellite Repeats; Sequence Analysis, DNA - methods; Software
• ISSN: 1367-4803; 1367-4811; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btx721

Abstract Motivation Microsatellites or Simple Sequence Repeats (SSRs) are short tandem repeats of DNA motifs present in all genomes. They have long been used for a variety of purposes in the areas of population genetics, genotyping, marker-assisted selection and forensics. Numerous studies have highlighted their functional roles in genome organization and gene regulation. Though several tools are currently available to identify SSRs from genomic sequences, they have significant limitations. Results We present a novel algorithm called PERF for extremely fast and comprehensive identification of microsatellites from DNA sequences of any size. PERF is several fold faster than existing algorithms and uses up to 5-fold lesser memory. It provides a clean and flexible command-line interface to change the default settings, and produces output in an easily-parseable tab-separated format. In addition, PERF generates an interactive and stand-alone HTML report with charts and tables for easy downstream analysis. Availability and implementation PERF is implemented in the Python programming language. It is freely available on PyPI under the package name perf_ssr, and can be installed directly using pip or easy_install. The documentation of PERF is available at https://github.com/rkmlab/perf. The source code of PERF is deposited in GitHub at https://github.com/rkmlab/perf under an MIT license. Supplementary information Supplementary data are available at Bioinformatics online.