Bioinformatics Support for High Throughput Transcriptomics

高通量转录组学的生物信息学支持

• 批准号: 10596965
• 负责人: RUCHIR SHAH
• 金额: $ 20万
• 依托单位: SCIOME, LLC
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-24 至 2022-09-23
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10596965
• 关键词: Archives; Bioinformatics; Businesses; Chemical Exposure; Chemicals; Contractor; Data; Data Reporting; Data Set; Detection; Dose; Gene Expression; Genes; Genetic Transcription; In Vitro; Kidney; Liver; Measures; Methods; National Institute of Environmental Health Sciences; Output; Pathway Analysis; Pathway interactions; Peer Review; Quality Control; Reproducibility; Research Activity; Sampling; Scientist; Series; Visualization; computer infrastructure; data analysis pipeline; data quality; differential expression; high throughput analysis; high throughput screening; in vivo; novel; programs; response; toxicant; transcriptomics

Major accomplishments of this task include: 1) Enhancement and deployment of TempO-Seq QC and data analysis pipeline. Sciome deployed a number of enhancements to detail a data quality control workflow for analysis of TempO-seq data (representative platform for HTT data). Enhancements included sample detection via various visualization and analysis approaches. the QA/QC data reports for HTT data averaged less than five business days. 2) Archival and management of high throughput transcriptomics data within the NIEHS computer infrastructure was performed by Sciome. These activities included detailed bioinformatics support to retrieve, organize, QC and archive original TempO-Seq data received by DNTP across various HTT projects. NIEHS Scientific IT, and other DNTP scientists and other contractors were involved in developing this accomplshment. 3) Analysis of HTT project #Tgmx15 TempO-Seq study was conducted by Sciome for a detailed analysis of 20 chemicals involving liver and kidney TempO-Seq dataset including sequencing QC, outlier detection, normalization, extrapolation, DEG/DEP analysis, network analysis and BMDExpress dose response analysis for all 20 chemicals in liver and kidney. Sciome used a novel network analysis method to determine chemicals within the Tgmx15 study that are similar to each other; and also compared them with public signature data to predict modes of action. These data are being prepared in peer-reviewed manuscirpt form.

该任务的主要成就包括：1）TempO-Seq QC 和数据分析流程的增强和部署。 Sciome 部署了许多增强功能，以详细说明用于分析 TempO-seq 数据（HTT 数据的代表性平台）的数据质量控制工作流程。 增强功能包括通过各种可视化和分析方法进行样本检测。 HTT 数据的 QA/QC 数据报告平均不到五个工作日。 2) NIEHS 计算机基础设施内高通量转录组数据的归档和管理由 Sciome 进行。这些活动包括详细的生物信息学支持，以检索、组织、质量控制和存档 DNTP 在各个 HTT 项目中收到的原始 TempO-Seq 数据。 NIEHS Scientific IT、其他 DNTP 科学家和其他承包商参与了这一成果的开发。 3）HTT项目#Tgmx15 TempO-Seq研究的分析由Sciome进行，对涉及肝脏和肾脏的20种化学物质TempO-Seq数据集进行了详细分析，包括对肝脏和肾脏中所有20种化学物质的测序QC、异常值检测、标准化、外推、DEG/DEP分析、网络分析和BMDExpress剂量反应分析。 Sciome 使用一种新颖的网络分析方法来确定 Tgmx15 研究中彼此相似的化学物质；还将它们与公共签名数据进行比较以预测行动模式。 这些数据正在以同行评审的手稿形式准备。