Suppr超能文献

InSNP:一种用于自动检测和可视化单核苷酸多态性(SNP)和插入缺失(InDel)的工具。

InSNP: a tool for automated detection and visualization of SNPs and InDels.

作者信息

Manaster Carl, Zheng Weiyue, Teuber Markus, Wächter Stefan, Döring Frank, Schreiber Stefan, Hampe Jochen

机构信息

Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.

出版信息

Hum Mutat. 2005 Jul;26(1):11-9. doi: 10.1002/humu.20188.

Abstract

Availability of high quality SNP data is a rate-limiting factor in understanding the impact of genetic variability on gene function and phenotype. Although global projects like HAPMAP generate large numbers of SNPs in an even spacing throughout the human genome, many variation studies have a more focused approach: in the follow-up of positional association findings, candidate gene studies, and functional genomics experiments, knowledge of all variations in a limited amount of sequence (e.g., a gene) is needed. This leads to a large number of resequencing experiments, for which there is a surprising lack of analysis software. We have thus developed specialized software (InSNP) for targeted mutation detection and compared its performance to Polyphred and Mutation Surveyor using 28 amplicons. Out of a total of 579 (InSNP), 644 (Polyphred), and 526 (Mutation Surveyor) SNP predictions, 39 SNPs were confirmed by human expert inspection, with five SNPs missed by Polyphred and one missed by InSNP using the default settings. For InDel detection, out of 70 (InSNP), 28 (Polyphred), and 693 (Mutation Surveyor) InDel predictions, two InDels were confirmed by human expert inspection, with one InDel missed by Polyphred. InSNP provides a user-friendly interface with better functionality for mutation detection than general-purpose sequence handling software. It provides similar SNP detection sensitivity and specificity as the public domain and commercial alternatives in the investigated dataset. We hope that InSNP lowers the barriers to the use of automated mutation detection software and aids in the improvement of the efficiency of such experiments. The Windows installer (setup) program and sample datasets are available at www.mucosa.de/insnp/.

摘要

高质量单核苷酸多态性(SNP)数据的可用性是理解基因变异对基因功能和表型影响的一个限制因素。尽管像HAPMAP这样的全球项目在整个人类基因组中以均匀间隔生成了大量SNP,但许多变异研究采用的是更具针对性的方法:在位置关联研究结果的后续跟进、候选基因研究以及功能基因组学实验中,需要了解有限序列(如一个基因)中的所有变异。这导致了大量的重测序实验,而令人惊讶的是,针对此类实验的分析软件却非常匮乏。因此,我们开发了专门用于靶向突变检测的软件(InSNP),并使用28个扩增子将其性能与Polyphred和Mutation Surveyor进行了比较。在总共579个(InSNP)、644个(Polyphred)和526个(Mutation Surveyor)SNP预测中,经人类专家检查确认了39个SNP,使用默认设置时,Polyphred遗漏了5个SNP,InSNP遗漏了1个SNP。对于插入缺失(InDel)检测,在70个(InSNP)、28个(Polyphred)和693个(Mutation Surveyor)InDel预测中,经人类专家检查确认了2个InDel,Polyphred遗漏了1个InDel。InSNP提供了一个用户友好的界面,与通用序列处理软件相比,其在突变检测方面具有更好的功能。在研究的数据集中,它提供了与公共领域和商业替代软件相似的SNP检测灵敏度和特异性。我们希望InSNP能够降低使用自动突变检测软件的门槛,并有助于提高此类实验的效率。Windows安装程序(设置)和示例数据集可在www.mucosa.de/insnp/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