Shared Resource-Bioinformatics Core

共享资源-生物信息学核心

• 批准号: 10560569
• 负责人: GRAHAM MCVICKER
• 金额: $ 27.3万
• 依托单位: SALK INSTITUTE FOR BIOLOGICAL STUDIES
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-12-31 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10560569
• 关键词: Big Data; Bioinformatics; Bioinformatics Shared Resource; Biological; Biology; Cancer Center; Cancer Center Support Grant; ChIP-seq; Computer software; Custom; Data; Data Analyses; Data Display; Data Set; Experimental Designs; Genes; Genomics; Goals; Grant; Manuscripts; Micro Array Data; Pathway Analysis; Pathway interactions; Procedures; Protein Isoforms; Publications; Publishing; RNA Splicing; Research; Resource Sharing; Services; Small RNA; Techniques; Training; Variant; Visualization; analysis pipeline; crosslinking and immunoprecipitation sequencing; data mining; differential expression; exome; experimental study; genetic variant; genome sequencing; genomic data; insight; member; next generation sequencing; novel; tool; transcriptome sequencing; whole genome

Bioinformatics Core Shared Resource - Project Summary/Abstract The Bioinformatics Core provides analytical, computational, and technical services for all aspects of genomics and bioinformatics research performed by Salk Cancer Center members. In the era of big data in biology, bioinformatics analysis is crucial for deriving biological insights from large and noisy high-throughput data. The goal of the Core has been to give Cancer Center members access to state-of-the-art bioinformatics expertise and support. Staff in the Core assist Cancer Center members with integrative analysis of sequencing datasets, provide software and tools that Cancer Center members can use to perform their own analyses, provide training in software use, and develop customized tools and pipelines for cutting-edge analyses. The Bioinformatics Core provides standard, best practice data analysis for commonly requested analyses such as: variant calling from whole exome and whole genome sequencing data, annotation of genomic variants, identification and annotation of peaks from ChIP-Seq, Clip-Seq, DamID, or 4C experiments, motif analysis from these peaks, identification of differentially expressed genes from RNA-Seq and small RNA-Seq datasets, identification and annotation of interactions from HiC datasets, identification of novel splice isoforms from RNA- Seq datasets, reanalysis of published or generated microarray datasets, integration of diverse genomics datasets (e.g., identifying correlations between differential ChIP-Seq and differential RNA-Seq datasets) and pathway/overrepresentation analysis of analyzed genomic datasets. As needed, they also develop new tools and techniques for Cancer Center members whose projects push the boundaries of research, generate publication quality visualizations of analyses, and help prepare scientific manuscripts and grants containing bioinformatics or genomics components.

生物信息学核心共享资源 - 项目摘要/摘要 生物信息学核心为基因组学的各个方面提供分析、计算和技术服务 以及索尔克癌症中心成员进行的生物信息学研究。在生物学大数据时代， 生物信息学分析对于从大量且嘈杂的高通量数据中获得生物学见解至关重要。这 核心的目标是让癌症中心成员获得最先进的生物信息学专业知识 和支持。核心工作人员协助癌症中心成员对测序数据集进行综合分析， 提供癌症中心成员可以用来执行自己的分析的软件和工具， 软件使用培训，并开发用于尖端分析的定制工具和管道。这 生物信息学核心为常见要求的分析提供标准、最佳实践数据分析，例如： 来自全外显子组和全基因组测序数据的变体调用，基因组变体的注释， 对 ChIP-Seq、Clip-Seq、DamID 或 4C 实验中的峰进行识别和注释，基序分析 这些峰，从 RNA-Seq 和小 RNA-Seq 数据集中鉴定差异表达基因， 从 HiC 数据集中识别和注释相互作用，从 RNA 中识别新的剪接亚型 Seq 数据集、已发布或生成的微阵列数据集的重新分析、不同基因组学的整合 数据集（例如，识别差异 ChIP-Seq 和差异 RNA-Seq 数据集之间的相关性）和 对分析的基因组数据集进行通路/过度代表性分析。根据需要，他们还开发新工具 为癌症中心成员提供技术和技术，他们的项目突破了研究的界限，产生 出版质量的分析可视化，并帮助准备包含以下内容的科学手稿和资助 生物信息学或基因组学成分。