Interleukin-6 is critical in the development of gcn2-mutation associated pulmonary veno-occlusive disease in mice
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: 5 × GCN2KO lung, CD45+ vs 5 × WT lung, CD45+ vs 3 × WT lung, CD45 vs 3 × GCN2KO lung, CD45Groups 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.
Read the full summary ↓
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 GSE294702_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 PRJNA1251345 and SRA study SRP578953. 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.
- GSM8917194 G1: GCN2KO lung, CD45+ GCN2KO lung, CD45+
- GSM8917195 G2: WT lung, CD45+ WT lung, CD45+
- GSM8917196 G3: GCN2KO lung, CD45+ GCN2KO lung, CD45+
- GSM8917197 G4: WT lung, CD45+ WT lung, CD45+
- GSM8917198 G5: WT lung, CD45+ WT lung, CD45+
- GSM8917199 G6: WT lung, CD45- WT lung, CD45
- GSM8917200 G7: GCN2KO lung, CD45+ GCN2KO lung, CD45+
- GSM8917201 G8: GCN2KO lung, CD45- GCN2KO lung, CD45
- GSM8917202 G9: WT lung, CD45+ WT lung, CD45+
- GSM8917203 G10: WT lung, CD45- WT lung, CD45
- GSM8917204 G11: GCN2KO lung, CD45+ GCN2KO lung, CD45+
- GSM8917205 G12: GCN2KO lung, CD45- GCN2KO lung, CD45
- GSM8917206 G13: WT lung, CD45+ WT lung, CD45+
- GSM8917207 G14: WT lung, CD45- WT lung, CD45
- GSM8917208 G15: GCN2KO lung, CD45+ GCN2KO lung, CD45+
- GSM8917209 G16: GCN2KO lung, CD45- GCN2KO lung, CD45
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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.