Bioinformatics, Biostatistics, and Image Analyses Core

生物信息学、生物统计学和图像分析核心

• 批准号: 10443724
• 负责人: Xiaole Shirley Liu
• 金额: $ 26.62万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-12 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10443724
• 关键词: ATAC-seq; Algorithmic Analysis; Algorithms; Animal Model; Animals; Applications Grants; Automobile Driving; Behavior; Bioinformatics; Biometry; Cell Line; Cells; ChIP-seq; Clinical; Clinical Data; Clinical Pathology; Clinical Trials; Collaborations; Computer Analysis; Coupled; Dana-Farber Cancer Institute; Data; Data Analyses; Data Set; Development; Diagnostic; Ensure; Epigenetic Process; Experimental Pathology; Generations; Genes; Genetic Screening; Genetic Transcription; Genomics; Goals; Hospitals; Image Analysis; Imaging Techniques; Immunofluorescence Immunologic; Immunohistochemistry; Immunotherapy; Individual; International; Journals; Malignant Neoplasms; Pathologist; Pharmaceutical Preparations; Phenotype; Program Research Project Grants; Quality Control; Records; Research; Research Design; Research Personnel; Resistance; Sampling; Shapes; Statistical Data Interpretation; T-cell receptor repertoire; Tissues; Validation; Woman; Work; blocking factor; computerized tools; data integration; data management; data sharing; design; digital imaging; editorial; epigenomics; experimental study; genome-wide; imaging biomarker; improved; insight; large datasets; melanoma; power analysis; programs; single-cell RNA sequencing; sound; therapy resistant; tool; transcriptome; transcriptome sequencing; transcriptomics; tumor; tumor immunology; tumor-immune system interactions

Project Summary The goals of the Bioinformatics, Biostatistics, and Image Analyses Core are to provide biostatistical and bioinformatics expertise and computational tools for genome-scale transcriptomic and epigenomic studies, as well as perform multiplex immunofluorescence profiling and analyses of tumor immune microenvironments. The work of the Core will ensure optimal study designs, quality control, and statistical analyses of data, as well as sophisticated integration of data across different datasets and animal species. Analyses of ChIP-seq and RNA- seq data will utilize state-of-the-art algorithms developed by a Core Co-Director. Multiplex immunofluorescence is coupled with quantitative digital image analysis using tissue and individual cell segmentation and cell phenotype analysis algorithms. The specific aims of this Core are: 1) Support transcriptomic (RNA-seq) and epigenomic (ATAC-seq and ChIP- seq) analyses of cells and tumors upon gene and/or drug perturbation. 2) Support single-cell RNA-seq and T- cell receptor repertoire data analyses. 3) Support genetic screen data analyses and integration. 4) Conduct multiplex immunohistochemistry profiling and analyses. 5) Integrate data on cell lines and animal models with data from clinical samples and clinical trials. 6) Provide biostatistical and power analyses support. 7) Support data management and sharing among the different projects The rigorous computational tools and analyses provided by the Core will maximize confidence in validation of results and generation of new hypotheses toward the objective of overcoming resistance to targeted and immunotherapies for melanoma.

项目概要 生物信息学、生物统计学和图像分析核心的目标是提供生物统计和 用于基因组规模转录组和表观基因组研究的生物信息学专业知识和计算工具，例如 以及对肿瘤免疫微环境进行多重免疫荧光分析和分析。这 核心的工作将确保最佳的研究设计、质量控制和数据统计分析，以及 跨不同数据集和动物物种的数据的复杂集成。 ChIP-seq 和 RNA 分析 seq 数据将利用由核心联合总监开发的最先进的算法。多重免疫荧光 与使用组织和单个细胞分割和细胞的定量数字图像分析相结合 表型分析算法。 该核心的具体目标是：1）支持转录组（RNA-seq）和表观基因组（ATAC-seq 和 ChIP- seq）根据基因和/或药物扰动对细胞和肿瘤进行分析。 2) 支持单细胞RNA-seq和T- 细胞受体库数据分析。 3) 支持基因筛查数据分析和整合。 4) 行为 多重免疫组织化学分析和分析。 5) 将细胞系和动物模型的数据与 来自临床样本和临床试验的数据。 6) 提供生物统计和功效分析支持。 7) 支持 不同项目之间的数据管理和共享 核心提供的严格计算工具和分析将最大限度地提高验证的信心 结果并产生新的假设，以克服对有针对性的和 黑色素瘤的免疫疗法。