Comprehensive Analysis and Multi-Omics Data Integration for Cancer-Related Studies

项目摘要/摘要 我是实验和研究中心的研究助理和生物信息学经理 西德尼·基梅尔综合癌症中心的计算基因组学核心 (ECGC)在约翰霍普金斯大学。该核心提供全面的生物信息学 为癌症中心和彭博基梅尔研究所的成员提供支持 癌症免疫治疗(BKI)，包括标准信息学和创新 分析管道的发展。对于这项工作，我带来了基因组数据分析方面的专业知识 方法通过我领导的几种肿瘤类型的DNA甲基化分析 用于癌症基因组图谱(TCGA)。作为ECGC的生物信息学经理， 我负责监督日常生物信息学服务，并支持 数据集成、注释和高通量数据分析领域的研究人员。 以这个身份，我开发了支持许多癌症的生物信息学软件工具 研究活动。我与许多研究人员合作，研究这两种癌症 中心和BKI。我重点介绍了此应用程序中的三个关键协作，以说明 我的研究档案。例如，(1)我在综合项目中发挥了关键作用 FEST的T细胞受体测序数据分析(功能扩展 特异性T细胞，http://www.stat-apps.onc.jhmi.edu/FEST/)法。(2)我表演 综合分析多重数据以找到更好的生物标志物来预测对 除密度外同时表达免疫标记物的癌症免疫治疗 以及表达这些标志物的细胞的空间相关性。(3)我是铅分析员 确定染色质结构如何与基因相关的基础肿瘤生物学 表达和选择性剪接。在这个R50奖项的支持下，我将把我的 当前管道技术发展到最先进的单电池测量技术 和数据集成技术，并培训未来的生物信息学分析师以受益 在癌症中心和BKI进行的各种癌症相关研究。

Project Summary/Abstract I am a Research Associate and Bioinformatics Manager of The Experimental and Computational Genomics Core in the Sidney Kimmel Comprehensive Cancer Center (ECGC) at Johns Hopkins University. This Core offers comprehensive bioinformatics support to members of both the Cancer Center and the Bloomberg~Kimmel Institute for Cancer Immunotherapy (BKI), including both standard informatics and innovative analysis pipeline development. To this work, I bring expertise in genomics data analysis methods through my role leading the DNA methylation analysis in several tumor types for The Cancer Genome Atlas (TCGA). In my role as Bioinformatics Manager of ECGC, I oversee day-to-day bioinformatics services and supports the bioinformatics needs of investigators in areas of data integration, annotation, and high-throughput data analysis. In this capacity, I develop bioinformatics software tools to support many cancer research activities. I collaborate with a number of investigators across both the cancer center and BKI. I highlight three key collaborations in this application as illustrative of my research portfolio. For example, (1) I played a key role in the comprehensive analysis of T-cell receptor sequencing data for the FEST (Functional Expansion of Specific T cells, http://www.stat-apps.onc.jhmi.edu/FEST/) assay. (2) I perform integrative analysis of multiplex data to find better biomarkers to predict response to cancer immunotherapy using both expression of immune markers in addition to density and a spatial correlation of cells expressing those makers. (3) I am lead analyses for basic tumor biology to determine how chromatin structure is associated with gene expression and alternative splicing. With the support of this R50 award, I will extend my current pipeline development to state of the art single cell measurement technologies and data integration techniques and train future bioinformatics analysts to benefit various cancer-related studies throughout the cancer center and BKI.