TASUKE+:一个基于网络的平台,用于探索GWAS结果和大规模重测序数据

M. Kumagai, Daiki Nishikawa, Y. Kawahara, Hironobu Wakimoto, Ryutaro Itoh, Norio Tabei, Tsuyoshi Tanaka, T. Itoh
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引用次数: 17

摘要

最近测序技术的革命性进步使得以经济有效的方式获得大量基因组级序列数据成为可能,并彻底改变了分子生物学研究。为了利用这些序列数据,全基因组关联研究(GWASs)变得越来越重要。因此,迫切需要开发一种可视化工具,以实现高效的数据检索,将GWAS结果与各种信息集成,并快速公开此类大规模基因型和表型数据。我们开发了基于web的基因组浏览器TASUKE+ (https://tasuke.dna.affrc.go.jp/),该浏览器具有以下功能:(i)交互式GWAS结果可视化,包括基因组重测序数据和注释信息,(ii) PCR引物设计,(iii)系统发育树重建和(iv)通过web共享数据。GWAS结果可以以交互和可扩展的方式与多态性数据、读取深度和注释信息并行显示。用户可以为感兴趣的多态性位点设计PCR引物。此外,可以重建任何区域的分子系统发育树,以便可以直观地了解所检查基因组之间的总体关系。所有功能都是通过用户友好的基于web的界面实现的,因此研究人员可以在没有广泛生物信息学知识的情况下轻松地与远程合作者共享数据。
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TASUKE+: a web-based platform for exploring GWAS results and large-scale resequencing data
Abstract Recent revolutionary advancements in sequencing technologies have made it possible to obtain mass quantities of genome-scale sequence data in a cost-effective manner and have drastically altered molecular biological studies. To utilize these sequence data, genome-wide association studies (GWASs) have become increasingly important. Hence, there is an urgent need to develop a visualization tool that enables efficient data retrieval, integration of GWAS results with diverse information and rapid public release of such large-scale genotypic and phenotypic data. We developed a web-based genome browser TASUKE+ (https://tasuke.dna.affrc.go.jp/), which is equipped with the following functions: (i) interactive GWAS results visualization with genome resequencing data and annotation information, (ii) PCR primer design, (iii) phylogenetic tree reconstruction and (iv) data sharing via the web. GWAS results can be displayed in parallel with polymorphism data, read depths and annotation information in an interactive and scalable manner. Users can design PCR primers for polymorphic sites of interest. In addition, a molecular phylogenetic tree of any region can be reconstructed so that the overall relationship among the examined genomes can be understood intuitively at a glance. All functions are implemented through user-friendly web-based interfaces so that researchers can easily share data with collaborators in remote places without extensive bioinformatics knowledge.
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