AtlasScope is a cross-species single-cell brain atlas designed for comparative transcriptomic analysis across diverse species. It provides insights into the variation of gene expression, gene sets, and cell-type distributions across evolutionary lineages. The dataset includes 9.6 million cells spanning 42 mammals, 45 fishes, 10 birds, 7 reptiles, 4 amphibians, and 26 invertebrates, offering a comprehensive resource for studying brain evolution at the molecular and cellular levels. AtlasScope offers four functional modules: sPandora (PAN DimensiOnal Rapid Analyzer for a single gene) allows users to explore the expression of individual genes across species; ePandora (PAN DimensiOnal Rapid Analyzer for an entire gene list) enables the investigation of curated gene sets from 28 different categories across various species; cPandora (PAN DimensiOnal Rapid Analyzer for a cell type) facilitates the comparison of cell-type proportions across species using stacked bar charts; and GeneLists provides differentially expressed gene lists for specific cell types, supporting enrichment analysis and functional exploration. For FASTQ files, we employed the Cell Ranger pipeline to perform read alignment, correct sequencing errors, and generate high-quality data for downstream single-cell RNA analysis. For publicly available datasets provided as original expression matrices, we processed them into AnnData objects using Scanpy, ensuring consistency across datasets. Additionally, for datasets stored in RDS format, we extracted the original count matrices, converted them into Loom files, and stored the corresponding metadata. These Loom files and metadata were subsequently read using Scanpy and converted into the H5AD format, enabling seamless integration and analysis within the BrainScope framework.