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scRNAseq Dataset of lungs from WT and Clec1a KO mice following primary or secondary E. coli lung infection

GSE326909 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/07/31 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 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
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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)
Pneumonia is associated with significant morbidity and mortality and is the leading cause of hospitalization and death worldwide. Sepsis exhibits phases of enhanced inflammation, alternating with immune suppression. Sepsis-induced immunosuppression is characterized by a deep remodelling of the myeloid immune compartment, leaving patients vulnerable to more severe forms of secondary infections.
Read the full summary ↓
Pattern Recognition Receptors (PRRs), such as the C Type Lectin Receptors (CLRs) family, are able to respond to a wide variety of endogenous and exogenous ligands, modulating a plethora of innate responses. We previously described the CLR CLEC-1, as a receptor of necrotic cells expressed by myeloid cells such as conventional Dendritic Cells type I (cDC1), and able to limit antigen presentation and downstream T cell response. Therefore, we evaluated the role of this novel immune checkpoint during the initial pro-inflammatory phase, and in the later inflammation resolution phase of sepsis. To do so, we performed E. coli lung primary and secondary infections in C57BL6 Clec1a deficient mice and analysed the immune response at day 1 and 3 following infections by scRNAseq.
This dataset
Open GSE326909 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 GSE326909_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 PRJNA1447939 and SRA study SRP689107. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.