Tumor Associated Macrophages And Microglia Drive Tumor Progression And Are Transcriptionally Shaped By Histone Mutations In Pediatric Diffuse Midline Glioma
Single-cell RNA-seq · mouse · 15 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 15 samples
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Microglia and monocyte-derived macrophages drive progression of pediatric high-grade gliomas and are transcriptionally shaped by histone mutationsImmunity · 2024
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE245716_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1029612 and SRA study SRP467181. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 15 more — browse all 15 samples with per-sample file links →
- GSE296797 CD38+CD93+ microglia and macrophages drive neuroinflammation through glycolysis-histone lactylation axis in multiple sclerosis model mice 17 samples shares macrophages, microglia, histone
- GSE290194 Repair-Associated Macrophages Increase after Early-phase Microglia Attenuation to Promote Ischemic Stroke Recovery [scRNA-Seq] 16 samples shares macrophages, microglia
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares microglia
- GSE159911 “Bench-to-Bedside and Back” analysis of NAFLD model reveals common transcriptomic shifts between mouse and human during disease progression 152 samples shares progression
- GSE300757 Efferocytosis induces proangiogenic function and chromatin remodeling in tumor-associated macrophages 127 samples shares macrophages
- GSE98969 Single cell RNA-seq identifies a unique microglia type associated with Alzheimer’s disease [RNA] 97 samples shares microglia
- GSE327428 GPR34 regulation of disease-associated microglial states in mice 96 samples shares microglia
- GSE302808 Depletion of Peripheral Monocytes Alters Long-Term Gene Expression in Microglia in a Murine Model of Traumatic Brain Injury 84 samples shares microglia
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.