Bioinformatics, Biostatistics, and Image Analyses Core

项目摘要 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学和 生物信息学专业知识和计算工具，用于基因组规模的转录和表观基因组研究，如 以及进行多重免疫荧光分析和肿瘤免疫微环境分析。这个 核心的工作将确保最佳研究设计、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-SEQ的分析 SEQ数据公司将使用由一名核心联合董事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。 这个核心的具体目标是：1)支持转录(RNA-SEQ)和表观基因组(ATAC-SEQ和CHIP-SEQ) 细胞和肿瘤对基因和/或药物扰动的分析。2)支持单细胞RNA-seq和T- 细胞受体谱系数据分析。3)支持遗传筛选数据分析和集成。4)行为 多重免疫组织化学分析。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)提供生物统计和动力分析支持。7)支持 不同项目之间的数据管理和共享 核心提供的严格的计算工具和分析将最大限度地提高对验证的信心 结果和产生新的假设，以实现克服对目标和目标的抗药性 黑色素瘤的免疫疗法。

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.