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Obesity-instructed TREM2-high macrophages identified by comparative analysis of diabetic mouse and human kidney at single-cell resolution [scRNA-seq: DKD_mouse]

GSE205592 Mus musculus (mouse) Single-cell RNA-seq 41 samples Submitted 2024/10/29 Platform GPL17021
At a glance

Single-cell RNA-seq · mouse · 41 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
41 samples: 10 conditions, mostly in triplicateGroups 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
Protective role for kidney TREM2(high) macrophages in obesity- and diabetes-induced kidney injuryCell reports · 2024
Summary (written by the submitters)
The cross-species molecular heterogeneity from mice to patients poses grand challenges for translational research endeavors. A high-fat diet (HFD) model and a genetic model (BTBR ob/ob) at different stand points were used to generate cell atlases of diabetic and obese mise. We identified a previously unrecognized, expanding Trem2-High macrophage population in kidneys of HFD mice that modeled human TREM2-high macrophages in obese patients. Taken together, our cross-species comparison highlights shared immune and metabolic cell-state changes.
Published in
Protective role for kidney TREM2(high) macrophages in obesity- and diabetes-induced kidney injury
Subramanian A, Vernon KA, Zhou Y et al. · Cell reports 2024 · PMID 38781074 · doi:10.1016/j.celrep.2024.114253
This dataset
Open GSE205592 in finder → Find more mouse RNA-seq datasets →
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.

Series matrix ↓
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 GSE205592_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA846680 and SRA study SRP378901. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38781074) ↗
Study design
10 conditions, mostly in triplicate
HFD ×7 WT ×7 BTBR_WT ×5 BTBR_ob ×5 2018-03-06-WT-C ×3 2018-03-06-ob-C ×3 BTBR_ob_section ×3 2018-03-01-WT-S ×2 +4 more

Supports a between-group comparison across 39 samples.

How we read this: 10 replicated groups read from 41 sample titles; they account for 39 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

+ 1 more — browse all 41 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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