CCR8 expression on regulatory T cells reveals trajectories of tissue adaptation and protects against myocardial infarction [bulk RNA-seq]
Single-cell RNA-seq · mouse · 16 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
- 16 samples: 4 × heart_CCR8 vs 4 × heart_CCR8+ vs 4 × MLN_CCR8 vs 4 × MLN_CCR8+Groups are read from the sample names, not from the paper. Check the list below.
- 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
- CCR8 Expression on Regulatory T Cells Reveals Trajectories of Tissue Adaptation and Protects Against Myocardial Infarction-Induced Tissue DamageCirculation · 2026
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 GSE291962_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 PRJNA1236261 and SRA study SRP570595. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 16 sample titles; they account for 16 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8845741 heart_CCR8-_1 heart_CCR8
- GSM8845742 heart_CCR8-_2 heart_CCR8
- GSM8845743 heart_CCR8-_3 heart_CCR8
- GSM8845744 heart_CCR8-_4 heart_CCR8
- GSM8845745 heart_CCR8+_1 heart_CCR8+
- GSM8845746 heart_CCR8+_2 heart_CCR8+
- GSM8845747 heart_CCR8+_3 heart_CCR8+
- GSM8845748 heart_CCR8+_4 heart_CCR8+
- GSM8845749 MLN_CCR8-_1 MLN_CCR8
- GSM8845750 MLN_CCR8-_2 MLN_CCR8
- GSM8845751 MLN_CCR8-_3 MLN_CCR8
- GSM8845752 MLN_CCR8-_4 MLN_CCR8
- GSM8845753 MLN_CCR8+_1 MLN_CCR8+
- GSM8845754 MLN_CCR8+_2 MLN_CCR8+
- GSM8845755 MLN_CCR8+_3 MLN_CCR8+
- GSM8845756 MLN_CCR8+_4 MLN_CCR8+
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- GSE267584 Enhancer-driven gene regulatory networks reveal transcription factors governing T cell adaptation and differentiation in the tumor microenvironment. 22 samples shares regulatory, adaptation
- GSE241770 ACSS2 mediates an epigenetic pathway to regulate maternal Beta-cell adaptation and progression of gestational diabetes (scRNA-Seq) 7899 samples shares adaptation
- GSE292261 A dynamic gene regulatory code drives synaptic development of hippocampal granule cells [SS2] 576 samples shares regulatory
- GSE290574 Gene Regulatory Networks Orchestrating Oocyte Fate Bifurcation in Primordial Follicles Revealed by Single-Cell Transcriptomics 386 samples shares regulatory
- GSE228457 IL-7 mediated immunoregulatory feedback loop promotes dampening of immune effector functions by hypoinflammatory monocytes. 305 samples shares regulatory
- GSE217662 Decoding Trp53 regulatory program with knockout cell transcriptomic landscape analyses [scRNA-seq] 247 samples shares regulatory
- GSE218178 Adaptation to an acid microenvironment promotes pancreatic cancer organoid growth and drug resistance 183 samples shares adaptation
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.