Suppr超能文献

TRcaller:一种用于在大规模平行测序读数中进行精确和超快速串联重复变异基因分型的新型工具。

TRcaller: a novel tool for precise and ultrafast tandem repeat variant genotyping in massively parallel sequencing reads.

作者信息

Wang Xuewen, Huang Meng, Budowle Bruce, Ge Jianye

机构信息

Center for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, United States.

Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, United States.

出版信息

Front Genet. 2023 Jul 18;14:1227176. doi: 10.3389/fgene.2023.1227176. eCollection 2023.

Abstract

Calling tandem repeat (TR) variants from DNA sequences is of both theoretical and practical significance. Some bioinformatics tools have been developed for detecting or genotyping TRs. However, little study has been done to genotyping TR alleles from long-read sequencing data, and the accuracy of genotyping TR alleles from next-generation sequencing data still needs to be improved. Herein, a novel algorithm is described to retrieve TR regions from sequence alignment, and a software program TRcaller has been developed and integrated into a web portal to call TR alleles from both short- and long-read sequences, both whole genome and targeted sequences generated from multiple sequencing platforms. All TR alleles are genotyped as haplotypes and the robust alleles will be reported, even multiple alleles in a DNA mixture. TRcaller could provide substantially higher accuracy (>99% in 289 human individuals) in detecting TR alleles with magnitudes faster (e.g., ∼2 s for 300x human sequence data) than the mainstream software tools. The web portal preselected 119 TR loci from forensics, genealogy, and disease related TR loci. TRcaller is validated to be scalable in various applications, such as DNA forensics and disease diagnosis, which can be expanded into other fields like breeding programs. Availability: TRcaller is available at https://www.trcaller.com/SignIn.aspx.

摘要

从DNA序列中识别串联重复(TR)变异具有理论和实际意义。已经开发了一些生物信息学工具来检测TRs或对其进行基因分型。然而,针对从长读长测序数据中对TR等位基因进行基因分型的研究较少,并且从下一代测序数据中对TR等位基因进行基因分型的准确性仍有待提高。在此,描述了一种从序列比对中检索TR区域的新算法,并开发了一个软件程序TRcaller,将其集成到一个门户网站中,用于从短读长和长读长序列、全基因组以及从多个测序平台生成的靶向序列中调用TR等位基因。所有TR等位基因都被基因分型为单倍型,并将报告稳健的等位基因,即使是DNA混合物中的多个等位基因。与主流软件工具相比,TRcaller在检测TR等位基因时可以提供更高的准确性(在289个人类个体中>99%),速度也快得多(例如,对于300倍的人类序列数据约为2秒)。该门户网站从法医、家谱和疾病相关的TR位点中预选了119个TR位点。TRcaller已被验证在各种应用中具有可扩展性,如DNA法医鉴定和疾病诊断,并可扩展到育种计划等其他领域。可用性:TRcaller可在https://www.trcaller.com/SignIn.aspx获取。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验