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LINC 数据集和工具入门。

Getting Started with LINCS Datasets and Tools.

机构信息

Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, New York.

School of Veterinary Medicine, University of California Davis, Davis, California.

出版信息

Curr Protoc. 2022 Jul;2(7):e487. doi: 10.1002/cpz1.487.

Abstract

The Library of Integrated Network-based Cellular Signatures (LINCS) was an NIH Common Fund program that aimed to expand our knowledge about human cellular responses to chemical, genetic, and microenvironment perturbations. Responses to perturbations were measured by transcriptomics, proteomics, cellular imaging, and other high content assays. The second phase of the LINCS program, which lasted 7 years, involved the engagement of six data and signature generation centers (DSGCs) and one data coordination and integration center (DCIC). The DSGCs and the DCIC developed several digital resources, including tools, databases, and workflows that aim to facilitate the use of the LINCS data and integrate this data with other publicly available data. The digital resources developed by the DSGCs and the DCIC can be used to gain new biological and pharmacological insights that can lead to the development of novel therapeutics. This protocol provides step-by-step instructions for processing the LINCS data into signatures, and utilizing the digital resources developed by the LINCS consortia for hypothesis generation and knowledge discovery. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Navigating L1000 tools and data in CLUE.io Basic Protocol 2: Computing signatures from the L1000 data with the CD method Basic Protocol 3: Analyzing lists of differentially expressed genes and querying them against the L1000 data with BioJupies and the Bulk RNA-seq Appyter Basic Protocol 4: Utilizing the L1000FWD resource for drug discovery Basic Protocol 5: KINOMEscan and the KINOMEscan Appyter Basic Protocol 6: LINCS P100 and GCP Proteomics Assays Basic Protocol 7: The LINCS Joint Project (LJP) Basic Protocol 8: The LINCS Data Portals and SigCom LINCS Basic Protocol 9: Creating and analyzing signatures with iLINCS.

摘要

LINCS(整合网络细胞特征图谱库)是 NIH 共同基金计划的一部分,旨在扩展我们对人类细胞对化学、遗传和微环境干扰的反应的认识。通过转录组学、蛋白质组学、细胞成像和其他高通量分析来测量对干扰的反应。LINCS 计划的第二阶段持续了 7 年,涉及 6 个数据和特征生成中心(DSGC)和 1 个数据协调和整合中心(DCIC)的参与。DSGC 和 DCIC 开发了几个数字资源,包括旨在促进 LINCS 数据使用并将这些数据与其他公开可用数据集成的工具、数据库和工作流程。DSGC 和 DCIC 开发的数字资源可用于获得新的生物学和药理学见解,从而开发新的治疗方法。本方案提供了将 LINCS 数据处理为特征并利用 LINCS 联盟开发的数字资源进行假设生成和知识发现的分步说明。© 2022 作者。Wiley Periodicals LLC 出版的《当代协议》。基本方案 1:在 CLUE.io 中导航 L1000 工具和数据基本方案 2:使用 CD 方法从 L1000 数据计算特征基本方案 3:分析差异表达基因列表并使用 BioJupies 和 Bulk RNA-seq Appyter 对 L1000 数据进行查询基本方案 4:利用 L1000FWD 资源进行药物发现基本方案 5:KINOMEscan 和 KINOMEscan Appyter 基本方案 6:LINCS P100 和 GCP 蛋白质组学测定基本方案 7:LINCS 联合项目(LJP)基本方案 8:LINCS 数据门户和 SigCom LINCS 基本方案 9:使用 iLINCS 创建和分析特征。

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