Padlock-Designed MOFs Triggers an 'Avalanche Effect' to Enhance Apoptosis and Suppress Metastasis in Central Nervous System Lymphoma

Description of the data and file structure
This dataset encompasses single - cell sequencing data of the brain, gut, and blood from mice with tumor models and brain from healthy mice. It analyzes the levels of gut - derived macrophages in the brains of tumor model mice and explores the mechanisms by which intestinal macrophages are recruited to the sites of brain tumors.
Files and variables
File: gut.zip
Description: This data was collected from the gut tissues of tumor model mice.
File: Healthy-brain.zip
Description: This data was collected from the brain tissues of healthy mice.
File: Blood.zip
Description: This data was collected from the blood of tumor model mice.
File: Tumour-Brain.zip
Description: This data was collected from the brain tissues of tumor model mice.
Code/software
Read counts of scRNA-seq were derived using CellRanger toolkit (v 6.1.2). GRCh38 were used as a reference genome to align reads. Combined read counts were analyzed using the Seurat workflow (v4.3.0) and visulated by ggplot2 (v3.5.2) in R enviroment(v4.3.1). Cells were filtered out based on three metrics for quality control: (1) the number of total UMI count was above 1200 and below 40000; (2) the number of detected genes was above 200 and below 8000; (3) the percentage of mitochondrial gene counts was less than 15%. Additionally, genes being detected in fewer than 50 cells and cells being detected with fewer than 3 genes were filtered out. Then, for each sample, data were normalized and scaled using SCT transform with 2,000 variable features, and cells were clustered using clusterProfiler following the standard Seurat protocol. Cell clustering was carried out using the FindCluster function based on a shared nearest neighbor modularity optimization on the top 20 principal components. The resolution was set at 0.7, determined computationally. UMAP were plotted, colored by sample, cluster, or selected features. Pseudotime trajectory and cell fate inference was done using Monocle3 (v1.3.1)