Apollo: Collaborative, Interactive Analytics and Annotation of Genome Variants

我们的目标是通过提供交互式探索来推进基因组分析 可视化工具使研究人员能够提炼、更正和扩充首字母 自动结果。对基因组进行测序的成本一直很高 在过去的十年里减少了几个数量级，自然的 其结果是，越来越多的研究人员正在对越来越多的 新的基因组，无论是在种群内还是在每个物种之间。因为 计算基因组分析仍然是一门不完美的艺术，每个新的外显子组或 测序后的基因组需要可视化。通过有效的可视化， 基因组解释可以利用人类的感知能力来 整合信息。网络阿波罗将提供一个易于使用的，基于网络的 为多个分布式用户提供高性能可视化的环境 用于交互探索基因组数据，以及生产所需的工具 为下游提供最大信息量的高度准确的批注 分析。这个项目将使新兴基因组的每一个成员 社区充分调动分子研究数据，无论是由 个人研究人员或从公共聚合网站上提供以受益 对遗传学和人类疾病的研究。 该项目将使研究人员能够(I)将变体可视化地投射到蛋白质上 显示以查看与蛋白质功能的交集，如活性位点和 评估生物影响的二级结构；(Ii)提高外显子的准确性 通过与相关蛋白质直接比较获得蛋白质编码转录本 综合多序列比对(MSA)观点；(Iii)探索基因组 使用关键站点的书签进行快速导航；(Iv)分析数据 通过折叠基因组来交互地将具有共同属性的基因 作为类比或共享表型以及它们内部的变体 视野；(Vi)与选定的团队成员安全地实时协作 通过互联网使用混合云存储私有数据和免费托管的服务器 以获取公共数据。

Our aim is to advance genome analysis by providing interactive exploratory visualization tools enabling researchers to refine, correct and augment initial automated results. The cost of sequencing a genome has been dramatically reduced by several orders of magnitude in the last decade, and the natural consequence is that more and more researchers are sequencing more and more new genomes, both within populations and across every species. Because computational genome analysis remains an imperfect art each new exome or genome that is sequenced requires visualization. With effective visualization, genome interpretation can take advantage of human perceptual capabilities to integrate information. Web Apollo will provide an easy to use, web-based environment offering multiple, distributed users high-performance visualization for interactive exploration of genome data, and the tools needed for producing highly accurate annotations that are maximally informative for downstream analysis. This project will enable every member of the burgeoning genomic community to fully mobilize molecular research data, whether collected by individual researchers or made available from public aggregation sites to benefit investigations into genetics and human diseases. This project will enable researchers to (i) Visually project variants onto protein displays to see intersection with protein features such as active sites and secondary structure to assess biological impact; (ii) Improve exonintron accuracy for protein coding transcripts via direct comparison to related proteins in an integrated multiple sequence alignment (MSA) view; (iii) Explore the genome using bookmarking of key sites for rapid navigation; (iv) Analyze the data interactively by folding of the genome to bring genes with shared attributes such as paralogy or shared phenotypes and the variants within them in the same visual field ; (vi) Collaborate securely in real-time with selected team members over the Internet using hybrid clouds for private data and freely-hosted servers for public data.