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Myeloid lineage (CD45+ CD11b+ cells) analysis sorted from stromal vascular fraction of visceral and subcutaneous adiposetissue in mice in different diet conditions or after rosiglitazone treatment

GSE267767 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2025/10/28 Platform GPL24247
At a glance

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: 8 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
Unlike visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) can play a protective role against the development of insulin resistance and metabolic dysfunction in obesity. These changes are associated with higher induction of pro-inflammatory programs and macrophage infiltration in VAT compared with SAT in obesity. Moreover, our results suggest that subcutaneous adipose tissue macrophages (ATMs) release small extracellular vesicles (sEVs) that can improve insulin sensitivity, opposite to the effect of visceral ATM sEVs in obesity.
Read the full summary ↓
This functional difference was associated with changes in the proportion of resident ATMs, as well as proinflammatory, recruited ATMs. To study the mechanism by which adipose tissue inflammation and macrophage infiltration are differentially regulated in SAT vs VAT, we performed single cell RNA sequencing (scRNA-seq) analysis in sorted live CD45+ CD11b+ myeloid cells from stromal vascular fraction (SVCs) of SAT and VAT of mice fed normal chow diet, high fat diet, or SVCs of HFD mice after the diet switch from high fat diet to normal chow diet, or treatment with insulin sensitizing, rosiglitazone.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE267767_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1112824 and SRA study SRP508448. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in duplicate
myeloid cells from visceral adiposetissue of … ×2 myeloid cells from subcutaneous adipose tissu… ×2 myeloid cells from visceral adiposetissue of … ×2 myeloid cells from subcutaneous adipose tissu… ×2 myeloid cells from visceral adiposetissue of … ×2 myeloid cells from subcutaneous adipose tissu… ×2 myeloid cells from visceral adiposetissue of … ×2 myeloid cells from subcutaneous adipose tissu… ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 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.

Samples in this study
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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.