CSIR - Centre for Cellular and Molecular Biology, Hyderabad, Telangana 500007, India.
Bioinformatics. 2018 Mar 15;34(6):943-948. doi: 10.1093/bioinformatics/btx721.
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.
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.
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 data are available at Bioinformatics online.
微卫星或简单重复序列 (SSR) 是存在于所有基因组中的 DNA 基序的短串联重复。它们长期以来一直被用于群体遗传学、基因分型、标记辅助选择和法医学等领域的各种目的。许多研究强调了它们在基因组组织和基因调控中的功能作用。尽管目前有几种工具可用于从基因组序列中识别 SSR，但它们存在显著的局限性。
我们提出了一种名为 PERF 的新算法，用于从任何大小的 DNA 序列中极其快速和全面地识别微卫星。PERF 比现有算法快几倍，使用的内存少 5 倍。它提供了一个干净灵活的命令行接口来更改默认设置，并以易于解析的制表符分隔格式生成输出。此外，PERF 生成带有图表和表格的交互式和独立的 HTML 报告，便于下游分析。
PERF 是用 Python 编程语言实现的。它在 PyPI 上以 perf_ssr 包的名称免费提供，并可以使用 pip 或 easy_install 直接安装。PERF 的文档可在 https://github.com/rkmlab/perf 上获得。PERF 的源代码存放在 GitHub 上，位于 https://github.com/rkmlab/perf 下，采用 MIT 许可证。
补充数据可在 Bioinformatics 在线获得。
