scRNA-seq of CD4+ T cells from mouse allergic airway inflammation model and human patients with eosinophilic chronic rhinosinusitis (ECRS)
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 3 × Human_ECRS_PBMC vs 3 × Human_ECRS_Polyp vs 2 × Mouse_control_lung vs 2 × Mouse_HDM_lungGroups 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
- Lipolysis-microlipophagy cascade regulated by adipose triglyceride lipase drives pathogenic adaptive type 2 immunityScience immunology · 2025
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 GSE249159_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 PRJNA1047575 and SRA study SRP475335. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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.
- GSM7927623 Mouse_control_lung_batch_1 Mouse_control_lung
- GSM7927624 Mouse_HDM_lung_batch_1 Mouse_HDM_lung
- GSM7927625 Mouse_control_lung_batch_2 Mouse_control_lung
- GSM7927626 Mouse_HDM_lung_batch_2 Mouse_HDM_lung
- GSM7927627 Human_ECRS_PBMC_1 Human_ECRS_PBMC
- GSM7927628 Human_ECRS_PBMC_2 Human_ECRS_PBMC
- GSM7927629 Human_ECRS_PBMC_3 Human_ECRS_PBMC
- GSM7927630 Human_ECRS_Polyp_1 Human_ECRS_Polyp
- GSM7927631 Human_ECRS_Polyp_2 Human_ECRS_Polyp
- GSM7927632 Human_ECRS_Polyp_3 Human_ECRS_Polyp
- GSE239704 NF-κB transcription factors RelA and c-Rel selectively control CD4+ T-cell function in multiple sclerosis and cancer 34 samples shares cd4
- GSE236107 Single cell transcriptomic analysis of acute and early ART-treated HIV-1-infected CD4+T cells from a reservoir-marking humanized mouse model 14 samples shares cd4
- GSE292898 Isolation and characterization of an islet-associated CD45- MHC class II+ cells using single cell RNA sequencing. 11 samples shares cd4
- GSE261475 Engineered CD47 protects T cells for enhanced antitumor immunity 8 samples shares cd4
- GSE295436 Hepatic leukemia factor directs tissue residency of proinflammatory CD4+ T cells 22 samples shares cd4
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.