Informatics Tools for High-throughput Analysis of Cancer Mutations

描述（由申请人提供）：大型肿瘤外显子组测序项目已经确定了非常大量的突变，其癌症相关性尚未被理解。为了开始解决这一需求，我们的团队已经开发了两个用于高通量癌症突变计算分析的web应用程序：癌症相关变体分析工具包（CRAVAT）和突变位置成像工具箱（MuPIT）。CRAVAT接受数百万个突变在单个批次上传和地图突变从基因组坐标到注释转录本和蛋白质。MuPIT目前接受多达2500个snv的批量上传，并从蛋白质数据库（PDB）中将基因组坐标映射到蛋白质的x射线晶体结构上。我们建议将CRAVAT和MuPIT合并并强化为一个单一的web应用程序，在这个应用程序中，我们将大大改进工具、用户界面、软件基础设施、与外部数据资源和社区使用的工具的集成以及对受保护数据的支持。web应用程序中所有工具的范围将被扩大，以处理在癌症外显子组中发现的各种小规模突变后果类型的分析。CRAVAT分析识别最有可能对蛋白质功能产生有害影响的突变，以及最有可能赋予癌细胞选择优势的突变（驱动因素），使用我们团队开发的分类器。分类器评分补充了注释，包括群体等位基因频率、肿瘤组织类型中以前发生的情况和基因功能类别，从而实现过滤（例如去除多态性）和优先级排序。还提供了基因水平的注释和评分，通过聚合来自队列中突变的分类器评分。MuPIT将突变从基因组位置映射到蛋白质结构上，并在蛋白质结构的背景下提供突变的交互式观察，并与a

DESCRIPTION (provided by applicant): Large tumor exome sequencing projects have identified a very large number of mutations whose cancer relevance is not yet understood. To begin to address this need, our team has produced two web applications for high-throughput computational analysis of cancer mutations: the Cancer-Related Analysis of VAriants Toolkit (CRAVAT) and the Mutation Position Imaging Toolbox (MuPIT). CRAVAT accepts millions of mutations in a single batch upload and maps mutations from genomic coordinates to annotated transcripts and proteins. MuPIT currently accepts batch uploads of up to 2500 SNVs and maps from genomic coordinates onto X-ray crystal structures of proteins from Protein Data Bank (PDB). We propose to combine and harden CRAVAT and MuPIT into a single web application, in which we will substantially improve the tools, user interface, software infrastructure, integration with external data resources and tools used by the community, and support for protected data. The scope of all tools in the web application will be broadened to handle analysis of the full range of small-scale mutation consequence types found in cancer exomes. CRAVAT analysis identifies mutations most likely to have deleterious impact on protein function and those that are most likely to confer a selective advantage to cancer cells (drivers), using classifiers developed by our team. Classifier scores are supplemented with annotations, including population allele frequencies, previous occurrence in tumor tissue types, and gene functional categories, enabling filtering (e.g. removing polymorphisms) and prioritization. Gene-level annotation and scoring, by aggregation of classifier scores from mutations in a cohort is also provided. MuPIT maps mutations from genomic positions onto to protein structures and provides interactive viewing of mutations in the context of protein structure, and in relation to a variety of annotations. To enable prioritization of interesting mutations and genes, the application provides a preview describing each structure and all available annotations (e.g., binding sites, experimental mutagenesis results, polymorphic and disease- associated variants that have been previously documented). After selecting a PDB of interest, the user is led to an interactive visualization page. An enhanced Jmol applet displays all SNVs mapped onto the structure. Frequently, many SNVs in the input list can be mapped onto a single structure, revealing clustering patterns around key functional sites. Based only on word-of-mouth, since the debut of the two applications in August 2012, CRAVAT has been utilized by 129 unique users from 39 countries, and it has analyzed 1,136 submitted jobs, totaling 27.9 million mutations. MuPIT has been utilized by 242 unique users from 25 countries, with 720 submitted jobs. (Source: Google Analytics).