Realtime visualization and analytics of epigenomic data using a serverless architecture

使用无服务器架构对表观基因组数据进行实时可视化和分析

基本信息

批准号：
10009580
负责人：
Amit U Sinha
金额：
$ 34.84万
依托单位：
BASEPAIR, INC.
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：
2020-04-10 至 2021-06-09
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10009580
关键词：
ATAC-seq Adopted Algorithms Antibodies Architecture Automobile Driving Benchmarking Bioinformatics Biological Assay Cell physiology Cells ChIP-seq Chromatin Chromatin Structure Code Complex Computer software Coupled Custom DNA DNA Methylation Data Data Analyses Data Set Data Sources Development Disease Epigenetic Process Feasibility Studies Feedback Future Gene Expression Genomics Goals Health Histones Human Industry Infrastructure K562 Cells Malignant Neoplasms Methodology Methods Modification Online Systems Outcome Pathway Analysis Performance Phase Phenotype Post-Translational Protein Processing Process Proteins Protocols documentation Publications Reaction Research Research Personnel Resolution Running Sampling Sampling Studies Scientist Sequence Alignment Services Signal Transduction Source Speed Technology Time Transcription Initiation Site Visualization Visualization software Work analysis pipeline bioinformatics pipeline bioinformatics tool chromatin immunoprecipitation cloud platform comparative cost data visualization drug development epigenomics experimental study human disease innovation multidimensional data multiple datasets new therapeutic target next generation sequencing novel novel drug class processing speed success technology development tool transcriptome sequencing user-friendly web services

项目摘要

PROJECT SUMMARY Epigenetics describes the study of phenotypic outcomes due to alterations in gene expression without changes to the coding DNA. The field has exploded in the past decade with the recognition that epigenetic factors (e.g. histone post-translational modifications, chromatin-associated proteins, DNA methylation) regulate gene expression and diverse downstream cellular processes, including the development of human disease. Next Generation Sequencing (NGS) studies of these epigenetic changes have enabled a more fundamental understanding of how chromatin structure impacts human health and revealed new targets for drug development. The importance of this field has driven remarkable advances in epigenomic profiling; however, innovations in methods to intelligibly interpret, compare, and visualize this mass of epigenetic data have lagged behind. The current framework for these tertiary analyses is slow, too technical for most users, and unable to process the increasingly complex queries that are required for epigenetic discovery. Basepair® is an industry leader in streamlined NGS analysis pipelines. Here, we will leverage this expertise with the development of EpiBeacon™, a serverless, user-friendly platform for rapid tertiary analysis of epigenetic data. In Aim 1, we will develop the EpiBeacon platform using the Amazon Web Services (AWS) Lambda service to instantly generate heatmaps of chromatin profiling data sourced from ENCODE. EpiBeacon will be uniquely compatible with the multiple rounds of iterative sampling required for tertiary analysis, and users will be able to dynamically adjust heatmap parameters and produce publication-ready figures in real time. In Aim 2, we will enable EpiBeacon with more sophisticated comparative analysis capabilities, which we will apply to answer an emerging problem in the field: whether antibodies and data from Chromatin ImmunoPrecipitation followed by NGS (ChIP-seq) are applicable to the novel chromatin profiling technology, CUT&RUN. CUT&RUN has the potential to supersede ChIP-seq as the standard in chromatin profiling, as it produces higher resolution data with fewer reads and reduced cell input vs. ChIP-seq. However, the methods underlying each approach are strikingly different, and antibodies that perform well in ChIP-seq may not be successful in CUT&RUN. We will work with EpiCypher®, a leader in chromatin technology development, to compare H3K4me3 and H3K27me3 antibody performance across ChIP and CUT&RUN experiments. The success of this Aim will validate EpiBeacon for comparative chromatin analyses and provide essential information for scientists adopting CUT&RUN. In Phase II, EpiBeacon will be expanded to other analyses (e.g. pathway analysis, motif discovery), other epigenomic assays (e.g. ATAC-seq), launch new tools to integrate multiple data sets (e.g. ChIP-seq and RNA- seq), and leverage publicly available datasets (e.g. NCBI SRA), which hold a wealth of epigenetic data that have been challenging to utilize with existing software. EpiBeacon will thus deliver the most rapid and user-friendly tertiary NGS analysis platform on the market, driving epigenetic discovery for advanced biomedical applications.

项目概要表观遗传学描述了对由于基因表达改变而导致的表型结果的研究，而无需随着人们认识到表观遗传因素，编码 DNA 的变化在过去十年中得到了爆炸性的发展。（例如组蛋白翻译后修饰、染色质相关蛋白、DNA 甲基化）调节基因表达和多种下游细胞过程，包括人类疾病的发展。对这些表观遗传变化的世代测序（NGS）研究使得我们能够更根本地了解了解染色质结构如何影响人类健康并揭示药物开发的新目标。该领域的重要性推动了表观基因组分析的显着进步。理解、比较和可视化大量表观遗传数据的方法已经落后。目前这些三级分析的框架速度很慢，对于大多数用户来说技术性太强，并且无法处理表观遗传发现所需的查询越来越复杂。 Basepair® 是简化 NGS 分析流程的行业领导者，在这里，我们将利用这一点。 EpiBeacon™ 开发的专业知识，这是一个无服务器、用户友好的平台，用于快速三级分析在目标 1 中，我们将使用 Amazon Web Services (AWS) 开发 EpiBeacon 平台。 Lambda 服务可立即生成来自 ENCODE 的染色质分析数据的热图。将与三级分析所需的多轮迭代采样独特地兼容，并且用户将能够动态调整热图参数并实时生成可供发布的数据。 2、我们将为EpiBeacon启用更复杂的对比分析功能，我们将其应用到回答该领域一个新出现的问题：抗体和数据是否来自染色质免疫沉淀其次是 NGS (ChIP-seq)，适用于新型染色质分析技术 CUT&RUN。有潜力取代 ChIP-seq 成为染色质分析的标准，因为它可以产生更高的分辨率与 ChIP-seq 相比，读取次数更少且细胞输入更少。但是，每种方法的基础方法是显着不同，在 ChIP-seq 中表现良好的抗体可能在 CUT&RUN 中不会成功。与染色质技术开发领域的领导者 EpiCypher® 合作，比较 H3K4me3 和 H3K27me3 ChIP 和 CUT&RUN 实验中的抗体性能该目标的成功将验证 EpiBeacon。用于比较染色质分析，并为采用 CUT&RUN 的科学家提供重要信息。第二阶段，EpiBeacon 将扩展到其他分析（例如通路分析、基序发现）、其他表观基因组分析（例如 ATAC-seq），推出新工具来整合多个数据集（例如 ChIP-seq 和 RNA- seq），并利用公开可用的数据集（例如 NCBI SRA），这些数据集拥有丰富的表观遗传数据 EpiBeacon 与现有软件一起使用一直是一项挑战，因此将提供最快速和用户友好的服务。市场上的三级 NGS 分析平台，推动先进生物医学应用的表观遗传学发现。