Informatics for Functional Integration of Heterogeneous Cancer Genome and Transcriptome Sequencing Data

项目摘要/摘要 该项目旨在开发两个新的信息学工具来实现功能集成 自体全外显子组DNA(WEX)和全转录组RNA测序 (WTX)在癌症研究和诊断中系统生成的数据 实验室。1)纹状体将去卷曲肿瘤基因组和转录图谱 同时从自体整体外显子组(WES)和整体转录组 测序(WTS)数据，并通过基因组转录组识别功能变异 综合分析。它将评估两者的肿瘤纯度和肿瘤内的异质性 DNA和RNA数据，量化肿瘤等位基因特异性拷贝数(ASCN)图谱和 肿瘤等位基因特异性表达水平(ASEL)，并整合ASCN和ASEL特征以 鉴定功能性基因组变异。2)TransBreak将扩展我们久负盛名的 基于MER的组装方法(novoBreak，自然方法2016)，以检测新的 肿瘤WTS数据和新抗原预测中的转录切割连接和变异 来自组装的新的RNA异构体。这些工具的输出将彻底 使用计算和实验方法通过联合体进行评估，例如 TCGA和BASE/临床合作者使用已建立的方案和资源。这个 建议的工具将按照最佳软件工程实践进行开发，并将 通过公开的网站以开源的方式发布。

Project Summary/Abstract This project aims to develop two novel informatics tools to enable functional integration of autologous whole exome DNA (WEX) and whole transcriptome RNA sequencing (WTX) data that are being systematically generated in cancer research and diagnostic labs. 1) Texomer will deconvolute the tumor genomic and transcriptomic profiles simultaneously from autologous bulk whole exome (WES) and whole transcriptome sequencing (WTS) data, and identify functional variants through genome-transcriptome integrative analysis. It will estimate tumor purity and intra-tumor heterogeneity in both DNA and RNA data, quantify tumor-allele-specific copy number (ASCN) profiles and tumor allele-specific expression levels (ASEL), and integrate ASCN and ASEL profiles to identify functional genomic variants. 2) TransBreak will expand our well-established k- mer-based assembly approach (novoBreak, Nature Methods 2016) to detect novel transcriptomic junctions and variants in the tumor WTS data and predict neo-antigens from assembled novel RNA isoforms. The output of these tools will be thoroughly evaluated using both computational and experimental means through consortia such as TCGA and bench/clinical collaborators using established protocols and resources. The proposed tools will be developed following best software engineering practices and will be released in open source via publicly available websites.