Institute for Advanced Study, Chengdu University, Chengdu, Sichuan 610106, China.
Rehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646099, China.
Bioinformatics. 2018 Feb 15;34(4):681-683. doi: 10.1093/bioinformatics/btx665.
Microsatellites are found to be related with various diseases and widely used in population genetics as genetic markers. However, it remains a challenge to identify microsatellite from large genome and screen microsatellites for primer design from a huge result dataset. Here, we present Krait, a robust and flexible tool for fast investigation of microsatellites in DNA sequences. Krait is designed to identify all types of perfect or imperfect microsatellites on a whole genomic sequence, and is also applicable to identification of compound microsatellites. Primer3 was seamlessly integrated into Krait so that users can design primer for microsatellite amplification in an efficient way. Additionally, Krait can export microsatellite results in FASTA or GFF3 format for further analysis and generate statistical report as well as plotting.
Krait is freely available at https://github.com/lmdu/krait under GPL2 License, implemented in C and Python, and supported on Windows, Linux and Mac operating systems.
Supplementary data are available at Bioinformatics online.
微卫星与各种疾病有关，广泛应用于群体遗传学作为遗传标记。然而，从大型基因组中识别微卫星并从庞大的结果数据集筛选用于引物设计的微卫星仍然是一项挑战。在这里，我们介绍了 Krait，这是一种用于快速研究 DNA 序列中微卫星的强大而灵活的工具。Krait 旨在识别整个基因组序列上的所有类型的完美或不完美微卫星，并且也适用于复合微卫星的识别。Primer3 被无缝集成到 Krait 中，使用户能够以有效的方式为微卫星扩增设计引物。此外，Krait 可以将微卫星结果以 FASTA 或 GFF3 格式导出，以进行进一步分析，并生成统计报告和绘图。
Krait 可在 https://github.com/lmdu/krait 上免费获得，遵循 GPL2 许可证，使用 C 和 Python 实现，并支持 Windows、Linux 和 Mac 操作系统。
补充数据可在生物信息学在线获得。
