Single-Cell RNA Profiling of Glioblastoma Invasion Dynamics in Mouse Brain Slices

Sven Nelander's dataset provides single-cell RNA sequencing data from organotypic mouse brain slice cultures grafted with patient-derived glioblastoma cells. The 10.1 GB RDS files contain data from samples collected at 1, 3, and 6 days, formatted as Seurat objects with raw and normalized counts. It was last updated on March 17, 2026.

Use Cases

• Modeling tumor invasion dynamics based on longitudinal sampling at 1, 3, and 6 days.
• Analyzing host-tumor cell interactions based on separate data files for mouse and human cell populations.
• Characterizing transcriptional state evolution based on single-cell RNA sequencing data.
• Benchmarking cell type deconvolution algorithms based on the provided Seurat objects containing raw and SCTransform-normalized assays.

Strengths

• Longitudinal design with samples collected at three time points (1, 3, and 6 days).
• Data is provided as processed Seurat objects, including both raw counts and SCTransform-normalized assays.
• The dataset is large at 10.1 GB, suggesting substantial sequencing depth.
• Separates human (tumor) and mouse (host) cell populations into distinct files for focused analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.

Provenance

Source

figshare, authored by Sven Nelander.

Collection Method

Single-cell RNA sequencing (10x Genomics) of organotypic mouse brain slice cultures bearing grafted patient-derived glioblastoma cells.

Time Range

Experimental time points at 1, 3, and 6 days post-grafting.

Freshness

Last updated 2026-03 17 15:24:45.

Geography

Laboratory study; spatial coverage is not specified.