Rapid Acute Leukemia Genomic Profiling with CRISPR enrichment and Real-time long-read sequencing

项目摘要 母公司奖（1 R21 CA 280520 -01）旨在开发快速和具有成本效益的方法来检测急性 骨髓性白血病（AML）融合和突变，以改善患者的临床结局。家长奖 建立在基于CRISPR的单分子长读序测序测定（CSRL）的基础上， 通过纳入额外的预后和预测标志物，在AML中检测突变基因。改进的测定将是 使用已知的细胞系混合物和患者样本进行验证。父R21的目标1还将创建生物信息学 使用开源的Biodepot-workflow-builder（BERO）平台，支持当天数据分析的工作流程。 将扩展该平台以检测融合和DNA变体。父R21的目标2将比较我们的 检测试剂盒性能与存档标本上已建立的临床级检测试剂盒性能的比较，并评价 关于预后和治疗反应的定相数据和融合断点。父R21的目标3将 通过试点研究证明我们的分子谱分析和生物信息学平台的临床影响 对来自诊所的样本，当天检测和报告的便利性，以及当天影响的研究 结果可能对患者治疗产生潜在影响。我们的CSRL检测，结合新的生物信息学 方法，将建立潜在的使用在临床上的超快速同一天的信息分子分析 AML检测，以指导肿瘤学家立即实施治疗。 在本补充中，我们将采用软件工程最佳实践来扩展Bendash平台， 在运行时指定的不同平台上执行模块。生物信息学工作流程将能够 同时利用不同的资源，并充分利用增强的安全性和减少的数据传输， 本地设备，同时受益于云的可扩展性。这种混合云计算方法将 这对父R21有利，因为涉及大文件的步骤（碱基判定和比对）可以在本地完成， 支持GPU的笔记本电脑、服务器或专用设备，可将较小的文件传输到云端， 基于计算密集型深度学习的变体识别。目前，Becoms拥有专门的工作流程， 这些模块可以同时在云端和本地运行。该补充将允许用户指定 在运行时为模块提供一个执行平台，而无需重写工作流。我们将支持全职 研究软件工程师，并增加一名具有软件工程和云计算专业知识的新合作者 计算的此混合云实施将使用 父奖励和测试套件将作为工作流的一部分保存和分发。我们还将提供一个 登录服务，以简化在多个平台上执行所需的额外身份验证。所有软件 将是公开和开源的。这些改进将提供一个强大的开源平台， 其他多组学和成像数据工作流，以利用新兴的混合云和边缘计算 技术.

PROJECT SUMMARY The parent award (1R21CA280520-01) aims to develop fast and cost-effective methods of detecting Acute Myeloid Leukemia (AML) fusions and mutations to improve clinical outcomes for patients. The parent award builds on a CRISPR-based single molecule long-read sequencing assay (CSRL) to detect clinically relevant mutated genes in AML by including additional prognostic and predictive markers. The improved assay will be validated using known cell line mixes and patient samples. Aim 1 of the parent R21 will also create bioinformatics workflows to enable same day data analysis using the open-source Biodepot-workflow-builder (Bwb) platform. The Bwb platform will be extended to detect fusion and DNA variants. Aim 2 of the parent R21 will compare our assay performance to established clinical grade tests on archival specimens, and evaluate clinical impact of phasing data and fusion breakpoints on prognosis and treatment response. Aim 3 of the parent R21 will demonstrate the clinical impact of our molecular profiling assay and bioinformatics platform through a pilot study on samples from the clinic, ease of same day testing and reporting, and study of the impacts that same day results can potentially have on patient treatment. Our CSRL assay, combined with new bioinformatics approaches, will establish potential use in the clinic for an ultrarapid same-day informative molecular profiling assay for AML to guide oncologists for immediate therapy implementations. In this supplement, we will employ software engineering best practices to extend the Bwb platform to enable execution of modules on different platforms that are specified at runtime. Bioinformatics workflows will be able to simultaneously utilize different resources and leverage the enhanced security and reduced data transfer of local devices while benefiting from the scalability of the cloud. This hybrid cloud computing approach would be beneficial for the parent R21 as steps involving large files (basecalling and alignment) could be done locally on a GPU enabled laptop, server, or dedicated device resulting in the transfer of smaller files to the cloud for computationally intensive deep-learning based variant calling. Bwb currently has specialized workflows with modules that run simultaneously on the cloud and locally. The supplement will allow users to specify the execution platform for modules at runtime without the need to re-write the workflow. We will support a full-time research software engineer and add a new collaborator with expertise in software engineering and cloud computing. This hybrid cloud implementation will be applied and benchmarked using data generated in the parent award and the test suite will be saved and distributed as part of the workflow. We will also provide a single sign-on service to simplify the additional authentication needed for execution on multiple platforms. All software developed will be public and open-source. These improvements will provide a robust open-source platform for other multi-omics and imaging data workflows to leverage emerging hybrid cloud and edge computing technologies.