Aurisano Jillian, Reda Khairi, Johnson Andrew, Marai Elisabeta G, Leigh Jason
BMC Bioinformatics. 2015;16 Suppl 11(Suppl 11):S6. doi: 10.1186/1471-2105-16-S11-S6. Epub 2015 Aug 13.
The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets.
In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process.
BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.
可供比较基因组学研究人员使用的完整细菌基因组序列数据量正在迅速增加。然而，比较基因组学中的可视化——旨在实现跨基因组集合的分析任务——存在视觉可扩展性问题。虽然大型、多平铺和高分辨率显示器有可能解决可扩展性问题，但需要新的方法来利用此类环境，以便能够对大型基因组数据集进行有效的视觉分析。
在本文中，我们展示了细菌基因邻域研究环境（Bacterial Gene Neighborhood Investigation Environment，简称BactoGeNIE），这是一种用于在大型显示环境中进行比较基因邻域分析的新颖且具有视觉可扩展性的设计。我们通过对近700个大肠杆菌草图基因组的案例研究来评估BactoGeNIE，并展示从我们的设计过程中学到的经验教训。
与现有工具相比，BactoGeNIE能够处理数量大得多的邻域集合上的比较任务，并明确解决了视觉可扩展性问题。鉴于当前数据生成的趋势，这种类型的可扩展设计可能为基因组学中大规模比较研究问题的可视化设计提供参考。
