Integrated single-nucleus RNA-seq dataset of mouse brain from a multi-factorial benchmarking study
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Title: A systematic multi-factorial benchmarking reveals critical technical biases in single-nucleus RNA sequencing of the brain Author: Jin Ning Email: ningjin@stu.xjtu.edu.cn Date: 2026-05-12 Description: This dataset contains integrated Seurat objects (`.RDS` files) derived from a systematic multi-factorial benchmarking study of single-nucleus RNA sequencing (snRNA-seq) in the mouse brain. The data has undergone rigorous quality control and integration pipelines to ensure reproducibility and ease of use. File Structure: 1. `processed_clean_seuratobject.RDS`: The complete integrated dataset encompassing all samples and cell types identified in the study. 2. `processed_glutneuron_seuratobject.RDS`: A specialized subset filtered specifically for glutamatergic neuronal populations. 3. `processed_mapmycell_results.RDS`: A data frame containing the processed cell type annotation labels generated by the MapMyCell pipeline. 4. `Rscript_v1.1.zip`: Directory containing the source code (R scripts) and cell annotation files used for analysis in this study (Version 1.0). ## R Scripts for Reproducible Analysis The following R scripts (contained within `Rscript_v1.1.zip`) are provided to ensure the full reproducibility of our results: - `code_augar.R` - `code_celltype_DEG.R` - `code_celltype_shift.R` - `code_harmony_integration.R` - `code_mapmycell.R` - `code_marker_expression.R` - `code_upstream_corr.R` ## Cell Type Annotation Data The following files (used/generated by MapMyCell) are provided for cell type annotation: - `cl.df_CCN202307220.xlsx` - `count_datacsv_10xWholeMouseBrain(CCN20230722)_HierarchicalMapping_UTC_1765460371443.json`
