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

异质癌症基因组和转录组测序数据功能整合的信息学

基本信息

批准号：
10246262
负责人：
Ken Chen
金额：
$ 39.33万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10246262
关键词：
Alleles Autologous Autologous Tumor Cell Biological Cancer Center Cancer Diagnostics Classification Clinical Clinical Management Clinical Trials Communities DNA DNA sequencing Data Data Sources Development Dimensions Disease Etiology Genome Genomics Heterogeneity Immunogenomics Immunotherapy Induced Mutation Informatics Joints Knowledge Laboratories Large-Scale Sequencing Malignant Neoplasms Methods Molecular Molecular Diagnosis Molecular Target Mutation Mutation Detection Names Nature Normal Cell Output Patients Phenotype Protein Isoforms Proteins Protocols documentation RNA RNA Sequences RNA Splicing Research Research Personnel Resources Software Engineering Solid Specimen Technology The Cancer Genome Atlas Tissues Translating Variant anticancer research base bioinformatics tool cancer genome cancer genomics cancer vaccination cost effective design exome functional genomics genetic variant genome sequencing genome-wide informatics tool insertion/deletion mutation interest molecular diagnostics multiple omics neoantigens novel open source personalized diagnostics personalized therapeutic targeted treatment therapy development tool transcriptome transcriptome sequencing transcriptomics tumor tumor heterogeneity web site

项目摘要

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.

项目总结/摘要本项目旨在开发两种新的信息学工具，以实现功能整合自体全外显子组DNA（WEX）和全转录组RNA测序 (WTX)癌症研究和诊断中系统生成的数据 labs. 1)Texomer将对肿瘤基因组和转录组图谱进行去卷积同时从自体大量全外显子组（WES）和全转录组测序（WTS）数据，并通过基因组转录组识别功能变体综合分析它将评估肿瘤纯度和肿瘤内异质性， DNA和RNA数据，定量肿瘤等位基因特异性拷贝数（ASCN）谱，肿瘤等位基因特异性表达水平（ASEL），并整合ASCN和ASEL谱，鉴定功能性基因组变体。2)TransBreak将扩大我们的良好的k- 基于mer的组装方法（novoBreak，Nature Methods 2016）来检测新的肿瘤WTS数据中的转录组学连接和变体并预测新抗原来自组装的新型RNA异构体。这些工具的输出将彻底通过计算和实验手段进行评估， TCGA和实验室/临床合作者使用已建立的方案和资源。的拟议的工具将按照最佳软件工程做法开发，并将通过公开网站以开源方式发布。