Sempéré Guilhem, Philippe Florian, Dereeper Alexis, Ruiz Manuel, Sarah Gautier, Larmande Pierre
UMR InterTryp (CIRAD), Campus International de Baillarguet, 34398, Montpellier, Cedex 5, France.
South Green Bioinformatics Platform, 1000 Avenue Agropolis, 34934, Montpellier, Cedex 5, France.
Gigascience. 2016 Jun 6;5:25. doi: 10.1186/s13742-016-0131-8.
Exploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions.
Here we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats.
The Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.
探索基因组结构并分析其进化对于理解生物体的生态适应性至关重要。然而,随着下一代测序产生大量数据,在存储、搜索、共享、分析和可视化方面出现了计算挑战。在基因组变异研究方面尤其如此,目前缺乏可扩展且用户友好的数据探索解决方案。
在此,我们展示了Gigwa,这是一个基于网络的工具,它提供了一种简单直观的方式来通过不仅基于变异特征(包括功能注释)而且基于基因型模式对大量基因分型数据进行过滤,从而探索这些数据。数据存储依赖于MongoDB,它具有良好的可扩展性。Gigwa可以处理多个数据库,并且可以以单用户或多用户模式部署。此外,它提供了广泛的流行导出格式。
Gigwa应用程序适用于管理大量基因组变异数据。其用户友好的网络界面使这种处理广泛可用。它既可以简单地部署在工作站上,也可以用于为特定的研究人员群体提供共享数据门户。