CLIP Tool Kit (CTK): pipeline, user interface and tutorials for CLIP data analysis

CLIP 工具套件 (CTK)：用于 CLIP 数据分析的管道、用户界面和教程

• 批准号: 9294442
• 负责人: Chaolin Zhang
• 金额: $ 8万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-10 至 2019-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9294442
• 关键词: Algorithms; Biochemical; Bioinformatics; Biological Assay; Biology; Biotechnology; Code; Communities; Complex; Computer software; Custom; Data; Data Analyses; Dependency; Development; Disease; Feedback; Galaxy; Gene Expression Regulation; Genetic Transcription; Genome; Genomics; Gold; Hereditary Disease; High-Throughput Nucleotide Sequencing; Immunoprecipitation; Individual; Induced Mutation; Libraries; Maintenance; Malignant Neoplasms; Maps; Modeling; Names; Nature; Noise; Nucleotides; Online Systems; Output; Play; Post-Transcriptional RNA Processing; Process; Proteins; Protocols documentation; Publishing; RNA; RNA-Binding Proteins; RNA-Protein Interaction; Regulation; Research; Research Personnel; Resolution; Resources; Role; Series; Signal Transduction; Site; Software Engineering; Software Tools; Statistical Methods; System; Technology; Variant; base; crosslink; experience; experimental study; flexibility; genome-wide; improved; in vivo; mammalian genome; nervous system disorder; novel; prototype; tool; usability

Project summary CLIP Tool Kit (CTK): software package, user interface and tutorials for CLIP data analysis Multiple steps of gene expression regulation rely on co- and post-transcriptional processing of RNA through its interaction with RNA-binding proteins (RBPs). UV cross-linking and immunoprecipitation (CLIP) of protein- RNA complexes, followed by high-throughput sequencing of isolated RNA, has become a gold standard for mapping in vivo protein-RNA interactions on a genome-wide scale. However, there remains a lack of software tools that provide flexible, streamlined and comprehensive analysis of CLIP data that incorporates the most recent technical advancements of CLIP protocols and sequencing technology. Here we propose to develop the CLIP Tool Kit (CTK) to fill this gap by building on our extensive experience in this field and enhancing a prototype we have developed for our research over the years. Taking raw sequence reads coming off sequencers as input, CTK will perform a series of analyses using its three major components: 1) quality filtering and mapping of raw reads, followed by a stringent, model-based algorithm to collapse PCR duplicates to obtain unique CLIP tags; 2) an adaptive valley-seeking algorithm to define CLIP tag clusters and perform peak calling; and 3) a statistical method to determine the exact protein-RNA crosslink sites through analysis of crosslink induced mutation sites (CIMS) and truncation sites (CITS). We will implement several novel algorithms as well as important extensions to our current software package, to make significant improvement in accuracy and efficiency, and to keep up with advancement in CLIP protocols and sequencing technologies. In addition, we aim to improve the usability and dissemination of the software. We will implement an interface through Galaxy so that CTK can be integrated into this widely used bioinformatics workflow management system. Multiple tutorials for typical analysis pipelines will be developed and a user group will be established. Thus, this study will provide a valuable resource for the RNA biology research community.

项目摘要 CLIP工具包（CTK）：用于CLIP数据分析的软件包、用户界面和教程 基因表达调控的多个步骤依赖于RNA的共转录和转录后加工， 与RNA结合蛋白（RBP）相互作用。蛋白质的UV交联和免疫沉淀（CLIP）- RNA复合物，随后对分离的RNA进行高通量测序，已经成为检测RNA的金标准。 在全基因组范围内绘制体内蛋白质-RNA相互作用。然而，仍然缺乏软件， 提供灵活、精简和全面的CLIP数据分析的工具， CLIP协议和测序技术的最新技术进展。在这里，我们建议开发 CLIP工具包（CTK），以填补这一空白的基础上，我们在这一领域的丰富经验，并提高了 我们多年来为研究开发的原型。获取原始序列读数 作为输入，CTK将使用其三个主要组成部分进行一系列分析：1）质量 过滤和映射原始读数，然后使用严格的基于模型的算法来折叠PCR重复 以获得唯一的CLIP标签; 2）自适应谷搜索算法，以定义CLIP标签簇并执行 峰调用;和3）通过分析以下确定确切蛋白质-RNA交联位点的统计方法： 交联诱导突变位点（CIMS）和截短位点（CITS）。我们将实施几个新的 算法以及我们目前的软件包的重要扩展，使显着改善， 准确性和效率，并跟上CLIP协议和测序技术的进步。在 此外，我们亦致力改善该软件的可用性及推广情况。我们将实现一个接口 通过Galaxy，以便CTK可以集成到这个广泛使用的生物信息学工作流程管理中 系统将为典型的分析管道开发多个教程，并将建立一个用户组。 因此，本研究将为RNA生物学研究提供宝贵的资源。