Suppr超能文献

SDT:一种基于成对序列比对和同一性计算的病毒分类工具。

SDT: a virus classification tool based on pairwise sequence alignment and identity calculation.

作者信息

Muhire Brejnev Muhizi, Varsani Arvind, Martin Darren Patrick

机构信息

Department of Clinical Laboratory Sciences, University of Cape Town, Cape Town, South Africa.

Department of Clinical Laboratory Sciences, University of Cape Town, Cape Town, South Africa; School of Biological Sciences and Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand; Department of Plant Pathology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America.

出版信息

PLoS One. 2014 Sep 26;9(9):e108277. doi: 10.1371/journal.pone.0108277. eCollection 2014.

Abstract

The perpetually increasing rate at which viral full-genome sequences are being determined is creating a pressing demand for computational tools that will aid the objective classification of these genome sequences. Taxonomic classification approaches that are based on pairwise genetic identity measures are potentially highly automatable and are progressively gaining favour with the International Committee on Taxonomy of Viruses (ICTV). There are, however, various issues with the calculation of such measures that could potentially undermine the accuracy and consistency with which they can be applied to virus classification. Firstly, pairwise sequence identities computed based on multiple sequence alignments rather than on multiple independent pairwise alignments can lead to the deflation of identity scores with increasing dataset sizes. Also, when gap-characters need to be introduced during sequence alignments to account for insertions and deletions, methodological variations in the way that these characters are introduced and handled during pairwise genetic identity calculations can cause high degrees of inconsistency in the way that different methods classify the same sets of sequences. Here we present Sequence Demarcation Tool (SDT), a free user-friendly computer program that aims to provide a robust and highly reproducible means of objectively using pairwise genetic identity calculations to classify any set of nucleotide or amino acid sequences. SDT can produce publication quality pairwise identity plots and colour-coded distance matrices to further aid the classification of sequences according to ICTV approved taxonomic demarcation criteria. Besides a graphical interface version of the program for Windows computers, command-line versions of the program are available for a variety of different operating systems (including a parallel version for cluster computing platforms).

摘要

确定病毒全基因组序列的速度在持续加快,这对有助于对这些基因组序列进行客观分类的计算工具产生了迫切需求。基于成对遗传同一性度量的分类学分类方法具有高度自动化的潜力,并且越来越受到国际病毒分类委员会(ICTV)的青睐。然而,计算此类度量存在各种问题,这些问题可能会破坏其应用于病毒分类的准确性和一致性。首先,基于多序列比对而非多个独立的成对比对计算出的成对序列同一性,可能会导致随着数据集规模的增加同一性得分下降。此外,在序列比对过程中需要引入间隙字符来处理插入和缺失时,在成对遗传同一性计算过程中引入和处理这些字符的方法差异,可能会导致不同方法对同一组序列进行分类时出现高度不一致的情况。在此,我们介绍序列划分工具(SDT),这是一款免费且用户友好的计算机程序,旨在提供一种强大且高度可重复的方法,以客观地利用成对遗传同一性计算对任何核苷酸或氨基酸序列集进行分类。SDT可以生成可用于发表的成对同一性图和颜色编码的距离矩阵,以进一步根据ICTV批准的分类划分标准辅助序列分类。除了适用于Windows计算机的图形界面版本外,该程序的命令行版本适用于多种不同的操作系统(包括适用于集群计算平台的并行版本)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/895d/4178126/52a3cdcbaf7d/pone.0108277.g001.jpg

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