The Jackson Laboratory Senescence Tissue Mapping Center (JAX-Sen TMC) - Data Analysis Core

项目摘要/摘要数据分析核心 JAX-Sen小鼠组织映射中心(TMC)的数据分析核心(DAC)的目标是 构建小鼠细胞衰老的生物标志物数据集和分子图谱，并将这些数据传递给 SENet联盟组织和数据协调中心(CODCC)。生物分析核心(BAC) 将产生高分辨率、高含量的分子数据来表征细胞衰老 老年、近交系和遗传性小鼠肾脏、脂肪组织、胰腺、胎盘、心脏和下丘脑 不同的老鼠群。根据这些数据，DAC将为数据注释建立最先进的工作流程， 转录、成像和成像质谱学(IMS)数据的整理和分析，以构建细胞 衰老地图。DAC将在JAX和康涅狄格州大学与人类Sennet TMC的DAC密切合作 健康(Kapp-Sen TMC)、其他人和小鼠TMC以及CODCC开发和实施网络- 用于处理、分析和可视化Sennet数据的广泛标准。JAX-Sen DAC将利用 深度学习和计算机视觉在确定衰老细胞的强健生物标志物方面取得的重大进展 并绘制出它们的组织背景图。为了实现其目标，JAX-SEN DAC将实现严格且可重复的 数据注释、整理、处理和传播(目标1)。DAC将接收和集中 来自JAX-SEN BAC的测序、成像和IMS数据。它将自动化和强化QC程序以筛选 与BAC合作，用于批注和精选错误、批次效果和低质量样品。这个 DAC将基于公共社区标准、JAX-Sen基准和 参考数据集，然后集装箱化，以便与CODCC共享。根据这些数据，JAX-SEN DAC将 构建细胞衰老的生物标志物数据集和分子图谱(目标2)。DAC将部署分析 用于测序、图像和IMS数据的管道，带有已知和预期的衰老标记物，以识别和 从功能上诠释衰老细胞的新生物标记物，绘制其组织背景图，计算多样性 在衰老细胞群体内，并量化衰老细胞和邻近细胞之间的细胞间相互作用 细胞。DAC将汇总和集成这些数据和元数据，以构建高质量的蜂窝地图 衰老。最后，JAX-Sen DAC将以严格和可重现的开放方式传播JAX-Sen数据。 来源加工管道(目标3)。发改委将协调、标准化和传播数据处理 和分析管道与CODCC，遵守共同的社区标准，标准操作 程序，以及网络数据共享策略，以精确重现。我们将与Kapp-Sen合作 其他CODCC项目和TMC以确定协同效应，例如，在同一个CODCC项目和TMC上对人和鼠的生物标记进行调整 纸巾。

PROJECT SUMMARY/ABSTRACT DATA ANALYSIS CORE The objective of the Data Analysis Core (DAC) of the JAX-Sen mouse Tissue Mapping Center (TMC) is to construct biomarker datasets and molecular maps of cellular senescence in mice and deliver these data to the SenNet Consortium Organization and Data Coordinating Center (CODCC). The Biological Analysis Core (BAC) of JAX-Sen will generate high-resolution, high-content molecular data to characterize cellular senescence in mouse kidney, adipose tissue, pancreas, placenta, heart and hypothalamus in aged, inbred and genetically diverse mouse cohorts. From these data, the DAC will establish state-of-the-art workflows for data annotation, curation, and analysis of transcriptomic, imaging, and imaging mass spectrometry (IMS) data to build cellular senescence maps. The DAC will collaborate closely with the DAC of the human SenNet TMC at JAX and UConn Health (KAPP-Sen TMC), other human and mouse TMCs and the CODCC to develop and implement Network- wide standards for processing, analyzing and visualizing SenNet data. The JAX-Sen DAC will leverage significant recent advances in deep learning and computer vision to define robust biomarkers of senescent cells and map their tissue context. To achieve its goals, the JAX-Sen DAC will implement rigorous and reproducible data annotation, curation, processing, and dissemination (Aim 1). The DAC will receive and centralize sequencing, imaging, and IMS data from the JAX-Sen BAC. It will automate and harden QC procedures to screen for annotation and curation errors, batch effects, and low-quality samples in collaboration with the BAC. The DAC will implement the pipelines based on common community standards, benchmark on JAX-Sen and reference datasets, and then containerize for sharing with the CODCC. From these data, the JAX-Sen DAC will construct biomarker datasets and molecular maps of cellular senescence (Aim 2). The DAC will deploy analysis pipelines for sequencing, image and IMS data with known and prospective senescence markers to identify and functionally annotate novel biomarkers of senescent cells and map their tissue context, compute the diversity within senescent cell populations, and quantify cell-to-cell interactions between senescent cells and neighboring cells. The DAC will aggregate and integrate these data and metadata to build high-quality maps of cellular senescence. Finally, the JAX-Sen DAC will disseminate JAX-Sen data with rigorous and reproducible open- source processing pipelines (Aim 3). The DAC will harmonize, standardize, and disseminate data processing and analytic pipelines with the CODCC, adhering to common community standards, standard operating procedures, and the network data sharing policy to exact reproducibility. We will collaborate with KAPP-Sen and other CODCC projects and TMCs to identify synergy, e.g., align human and mouse biomarkers on the same tissues.