Macrophages display spatiotemporal specificity in intrahepatic cholangiocarcinoma and drive tumour progression via OSM and THBS1
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. 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
- 12 samples: 5 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.
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 GSE308574_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 PRJNA1311268 and SRA study SRP613762. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 5 replicated groups read from 12 sample titles; they account for 12 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.
- GSM9248505 WT-1 WT
- GSM9248506 WT-2 WT
- GSM9248507 D7-1 D7
- GSM9248508 D7-2 D7
- GSM9248509 D15-1 D15
- GSM9248510 D15-2 D15
- GSM9248511 D15-3 D15
- GSM9248512 D25-1 D25
- GSM9248513 D25-2 D25
- GSM9248514 D31-1 D31
- GSM9248515 D31-2 D31
- GSM9248516 D31-3 D31
- GSE309379 Nucleophosmin supports WNT-driven hyperproliferation and tumour initiation 111 samples shares osm
- GSE199680 Effect of simulated galactic cosmic radiation on mouse lung gene expression 37 samples shares osm
- GSE263042 scRNA-seq assessment of the impact of anti-IL6R and anti-OSM in a model of fibrotic lung disease during resolution (day 24) [NGS4659] 30 samples shares osm
- GSE263041 scRNA-seq assessment of the impact of anti-IL6R and anti-OSM in a model of fibrotic lung disease during fibrosis (day 14) [NGS4272] 30 samples shares osm
- GSE262966 Determining the impact of anti-IL6 and anti-OSM on macrophage and fibroblast biology in a model of fibrotic lung disease [NGS3341] 25 samples shares osm
- GSE244544 Characterization of an Osmr Conditional Knockout Mouse Model 18 samples shares osm
- GSE266023 Nrf2-mediated chromatin activation of hyperosmotic response genes attenuates heat-induced renal injury [RNA-seq] 16 samples shares osm
- GSE332663 Transcriptomic profiling of Cosmc-silenced Tn+ 4T1 cells-bearing triple-negative tumors in mice 12 samples shares osm
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.