Leveraging the Cloud for Splicing Discovery

项目总结： 选择性剪接是高等真核生物蛋白质组多样性最重要的贡献者之一。 当在癌症中被破坏时，错误剪接会导致健康细胞中没有观察到的独特的mRNA亚型。是这样的 癌症特异性剪接异构体代表了靶向癌症的潜在新抗原的未开发储存库 疫苗和免疫疗法。作为我们资助的NCI R01的核心组件，用于 跨越癌症的剪接体脆弱性“，我们一直在扩展和利用一种全面的剪接 分析管道，以确定跨人类癌症和健康组织的剪接脆弱性。关联的 通过这一努力建立起来的生物信息学工具旨在识别已知和新的癌症 亚型，提名关键的调控剪接因子，推断功能剪接-亚型影响和发现癌症- 新出现的免疫疗法或疫苗可以利用的特定新抗原。生物信息学工具 为了使这些发现与大型AltAnalyze开源项目的不同组件基本一致， 始于2008年。虽然AltAnalyze或其算法已在400多项已发表的研究报告中被引用，但重新- 在TCGA、GTEx和其他大型RNA-Seq汇编的规模上应用此工作流在历史上 需要大量的计算资源和时间来下载和重新处理数百TB的 以安全和合规的方式提供数据。新出现的基于云的解决方案有可能缓解 这些技术挑战通过以低成本简化了数千个前处理样品的计算来实现。 为应付这些挑战，我们建议： 目标1：简化和优化用于云的AltAnalyze。在这个目标中，我们将脱钩和优化 AltAnalyze的主要剪接分析组件可实现简化、有监督和无监督 癌症转录本的分析。AltAnalyze将打包为CWL管道，与Docker一起包装 并存放在DockStore中，实现了对云中拼接的快速全面分析。 目标2：将AltAnalyze.Cloud集成到Terra.bio中。为了实现对受控访问序列的直接分析- TCGA、TARGET、GTEX和其他主要的人类RNA测序数据集中的Level文件，我们将1)将我们的 CWL工作流到工作流描述语言(WDL)和2)建立用于集成的Terra工作流 使用AltAnalyze.Cloud进行拼接分析。AltAnalyze.Cloud将能够通过Terra网络运行 用于分析、进度跟踪、来源和结果共享的界面。这些功能将使 简化了用户和受控NIH存储在云中的数据集的重复使用。

PROJECT SUMMARY: Alternative splicing is among the most important contributors of proteomic diversity in higher order eukaryotes. When disrupted in cancer, mis-splicing results in unique mRNA isoforms not observed in healthy cells. Such cancer-specific splice isoforms represent an untapped reservoir of potential neoantigens for targeted cancer vaccines and immunotherapies. As a central component of our funded NCI R01 for “Unbiased identification of spliceosome vulnerabilities across cancer”, we have been extending and leveraging a comprehensive splicing analysis pipeline to define splicing vulnerabilities across human cancers and healthy tissues. The associated bioinformatics tools that are built-upon through this effort are designed to identify both known and novel cancer subtypes, nominate key regulatory splicing factors, infer functional splice-isoform impacts and discover cancer- specific neoantigens that can be exploited by emerging immunotherapies or vaccines. The bioinformatics tools to yield these discoveries largely consistent of distinct components of the large AltAnalyze open-source project, begun in 2008. While AltAnalyze or its algorithms have been cited in over 400 published research studies, re- applying this workflow at the scale of TCGA, GTEx and other large RNA-Seq compendiums have historically required significant computational resources and time to download and re-process hundreds of terabytes of data in a secure and compliant manner. New emerging cloud-based solutions have the potential to mitigate these technical challenges through streamlined compute of thousands of pre-processed samples at a low cost. To address these challenges, we propose to: Aim 1: Streamline and optimize AltAnalyze for the cloud. In this aim, we will decouple and optimize the primary splicing analysis components of AltAnalyze to enable streamlined supervised and unsupervised analysis of cancer transcriptomes. AltAnalyze will be packaged as a CWL pipeline, containerized with Docker and deposited in DockStore, enabling fast and comprehensive analyses of splicing in the cloud. Aim 2: Integrate AltAnalyze.cloud in Terra.bio. To enable direct analyses of controlled-access sequence- level files in TCGA, TARGET, GTEx and other major human RNA-sequencing datasets, we will 1) translate our CWL workflows to the Workflow Description Language (WDL) and 2) establish a Terra workflow for integrated splicing analysis using AltAnalyze.cloud. AltAnalyze.cloud will be able to be run through the Terra web interface for analysis, progress tracking, provenance and sharing of results. These features will enable streamlined re-use of user and controlled NIH deposited datasets in the cloud.