Core B: Advanced Bioinformatics Core

项目概要/摘要 核心B -高级生物信息学核心 高级生物信息学核心将为所有人提供创新和协作的计算支持。 三个项目，与高级蛋白质组学和基因组编辑核心密切合作。我们有 在开发基因组学的统计和生物信息学方法方面有几十年的经验， 蛋白质组学，包括用于分析和可视化的开源软件。近10年来，我们一直 与Srivastava，Bruneau和Black实验室密切合作，使用 数据量化和综合分析的最新工具。这些调查确定了几个关键的 心脏转录因子和染色质重塑蛋白，可以改变心脏发育， 变异的冠心病。然而，我们并不完全了解这些调节蛋白的机制， 功能从我们的初步研究中可以清楚地看出，突变改变了它们的亚细胞定位，蛋白质 相互作用和基因组占有率。蛋白质组学中的新技术（例如，APEX-MS）和基因组学（单- cell RNA-seq）有望揭示这些效应如何通过改变基因表达转化为疾病表型。 基因调控网络但量化和联合分析这些不同的数据存在重大挑战 类型高级生物信息学核心的目标是排除随机性、偏倚和混杂因素， 来自项目1-3的数据，使用现有的最先进的分析工具并开发新技术 在需要的地方。我们严格的统计方法将使核心能够整合内部和跨 项目，以解码冠心病病因的新机制，否则会错过。

PROJECT SUMMARY/ABSTRACT CORE B – ADVANCED BIOINFORMATICS CORE The Advanced Bioinformatics Core will provide innovative and collaborative computational support for all three Projects, in close partnership with the Advanced Proteomics and Genome Editing Cores. We have several decades of experience in developing statistics and bioinformatics methods for genomics and proteomics, including open source software for analysis and visualization. For nearly 10 years, we have been working closely with the Srivastava, Bruneau, and Black labs to dissect cardiac regulatory mechanisms using the latest tools for data quantification and integrative analysis. These investigations identified several key cardiac transcription factors and chromatin-remodeling proteins that can alter cardiac development and cause CHDs when mutated. Yet we do not fully understand the mechanisms through which these regulatory proteins function. It is clear from our preliminary studies that mutations alter their subcellular localization, protein interactions, and genomic occupancy. New techniques in proteomics (e.g., APEX-MS) and genomics (single- cell RNA-seq) promise to shed light on how these effects translate into disease phenotypes through altered gene regulatory networks. But there are major challenges quantifying and jointly analyzing these diverse data types. The objective of the Advanced Bioinformatics Core is to rule out chance, bias and confounding in the data from Projects 1–3, using state-of-art analyses tools when available and developing new techniques where needed. Our rigorous statistical approach will enable the Core to integrate data within and across projects to decode novel mechanisms of CHD etiology that would otherwise be missed.