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

项目总结/抽象数据分析核心 JAX-Sen小鼠组织绘图中心（TMC）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 SenNet联盟组织和数据协调中心（CODCC）。生物分析核心（BAC） JAX-Sen将产生高分辨率，高内容的分子数据，以表征细胞衰老， 小鼠肾脏、脂肪组织、胰腺、胎盘、心脏和下丘脑在老龄、近交和遗传 不同的小鼠队列。根据这些数据，DAC将建立最先进的数据注释工作流程， 管理和分析转录组、成像和成像质谱（IMS）数据，以构建细胞 衰老图谱DAC将与JAX和UConn的人类SenNet TMC的DAC密切合作 健康（KAPP-Sen TMC），其他人类和小鼠TMC和CODCC开发和实施网络- 处理、分析和可视化SenNet数据的广泛标准。JAX-Sen DAC将利用 最近在深度学习和计算机视觉方面取得了重大进展，以定义衰老细胞的强大生物标志物 并绘制它们的组织环境。为了实现其目标，JAX-Sen DAC将实现严格且可重复的 数据注释、策展、处理和传播（目标1）。DAC将接收并集中 JAX-Sen BAC的测序、成像和IMS数据。它将自动化和强化QC程序， 与BAC合作，针对注释和策展错误、批量效应和低质量样本进行分析。的 DAC将根据共同的社区标准、JAX-Sen基准和 参考数据集，然后容器化以与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，以及已知和预期的衰老标志物， 功能注释衰老细胞的新生物标志物并绘制其组织背景，计算多样性 在衰老细胞群体中，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将汇总和整合这些数据和元数据，以构建高质量的蜂窝地图。 衰老最后，JAX-Sen DAC将以严格和可复制的开放方式传播JAX-Sen数据， 源处理管道（Aim 3）。发展援助委员会将协调、标准化和传播数据处理 和分析管道与CODCC，坚持共同的社区标准，标准操作 程序和网络数据共享政策，以准确的再现性。我们将与KAPP-Sen合作， 其他CODCC项目和TMC，以确定协同作用，例如，将人类和小鼠的生物标志物在相同的 组织中

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.