CG-GRID: Computational Genetics Grid Resource for Interaction Discovery

描述（由申请人提供）：DNA测序技术的进步现在使得生成包含数百万个遗传属性的数据集变得实用和负担得起，这些数据集可以测试与疾病易感性的关联。在这样的高维数据集上搜索遗传相互作用的计算复杂性给全基因组关联研究（GWAS）带来了巨大的挑战。在该项目的第一阶段，由达特茅斯学院盖泽尔医学院首席研究员杰森·摩尔博士领导的Parabon研究小组开始通过开发分布式软件服务来分析大型GWAS数据集上的基因-基因相互作用，从而解决这些瓶颈问题。特别是，多因素降维（MDR）算法适用于Parabon(R) Crush”基因组挖掘应用。MDR被增强为使用Crush的机会进化搜索算法，在数千个计算节点上进行深入的云搜索，以识别与人类疾病终点或法医相关特征相关的基因-基因相互作用的复杂模式。由此产生的Crush-MDR软件即服务（SaaS）应用程序，可作为在线“云”服务或内部企业应用程序使用，通过模拟GWAS数据验证并显示出优异的性能特征，然后用于分析来自阿尔茨海默病神经成像倡议的数据集。在第二阶段，Parabon开发团队将扩展Crush-MDR服务的分析能力，并通过增强其Parabon(R) Frontier(R)计算平台（一种为高性能计算（HPC）应用而设计的商业云计算平台）来解决其他GWAS和下一代测序（NGS）瓶颈。我们的总体目标（源于与潜在客户的互动）是生产一个平台即服务（PaaS）解决方案，通过提供一套全面的云服务来极大地加速生物信息学研究，这些云服务共同解决了许多常见的生物信息学瓶颈和协作障碍。

DESCRIPTION (provided by applicant): Advances in DNA sequencing technology have now made it practical and affordable to generate datasets containing millions of genetic attributes that can be tested for association with disease susceptibility. The computational complexity of searching for genetic interactions over such high- dimensional datasets imposes great challenges for genome-wide association studies (GWAS). In Phase I of this project, the Parabon research team, led by principal investigator Dr. Jason Moore of Dartmouth College Geisel School of Medicine, began addressing these bottlenecks by developing a distributed software service for analyzing gene-gene interactions over large GWAS datasets. In particular, the multifactor dimensionality reduction (MDR) algorithm was adapted for use in the Parabon(R) Crush" genome mining application. MDR was augmented to employ Crush's opportunistic evolution search algorithm to enable deep, cloud-powered search, across thousands of compute nodes, to identify complex patterns of gene-gene interaction associated with human disease endpoints or forensically relevant traits. The resultant Crush-MDR Software as a Service (SaaS) application, which is available as an online "cloud" service or in-house enterprise application, was validated and shown to have excellent performance characteristics using simulated GWAS data, and then used to analyze a dataset from the Alzheimer's Disease Neuroimaging Initiative. In Phase II, the Parabon development team will extend the analytical capabilities of the Crush-MDR service and address other GWAS and next-generation sequencing (NGS) bottlenecks by enhancing its Parabon(R) Frontier(R) Compute Platform, a commercial cloud computing platform designed for high-performance computing (HPC) applications. Our overall objective (which was derived from interactions with prospective customers) is to produce a Platform as a Service (PaaS) solution that will greatly accelerate bioinformatics research by providing a comprehensive set of cloud services that collectively address many common bioinformatics bottlenecks and barriers to collaboration.