Multimodal imaging of the dynamic brain tumor microenvironment during glioblastoma progression and in response to treatment

• The deposited data have been generated by intravital imaging of glioma-bearing mice, which allows one to longitudinally track different cell types during tumor progression and response to therapy.
• Raw and processed data are divided into two folders, based on the cell lineage-tracing model used (either CX3CR1 or FLT3 lineage-tracing model).
• Each folder contains the raw imaging data and an R script folder.
• The raw imaging data consist of “Statistics”, parameters extracted after analysis with Imaris (.csv files). Each subfolder represents a specific timepoint for a unique imaging position in one individual mouse. Note that each segmented component (microglia (MG), second harmonic generation (SHG, measuring collagen), and tumor cells) have their own individual subfolder.
• The R script folder contains 3 files: the source file containing custom functions for processing and visualization; the processing file which combines imaging- and metadata, and transforms this into a single experimental object in R; and the output file which presents the analyses and visualizations of the data.

• 本数据集所收录的数据源自荷胶质瘤小鼠的活体成像实验，可实现肿瘤发生发展及治疗响应过程中多种细胞类型的纵向追踪。
• 原始数据与处理后数据根据所采用的细胞谱系示踪模型分为两个文件夹，对应CX3CR1谱系示踪模型与FLT3谱系示踪模型。
• 每个文件夹均包含原始成像数据及一个R脚本文件夹。
• 原始成像数据包含经Imaris分析后提取的统计参数（.csv格式文件）。每个子文件夹对应单只小鼠某一特定成像位点的特定时间节点。需注意，每个分割得到的组分——小胶质细胞（microglia, MG）、用于检测胶原的二次谐波生成（second harmonic generation, SHG）以及肿瘤细胞——均设有独立的子文件夹。
• 该R脚本文件夹包含3个文件：其一为自定义函数源码文件，用于数据处理与可视化；其二为处理脚本，可整合成像数据与元数据，并将其转换为R语言中的单一实验对象；其三为输出脚本，用于呈现数据的分析结果与可视化内容。