Single-Cell and Spatial Multi-omics Reveal Interferon Signaling in the Pathogenesis of Perianal Fistulizing Crohn’s Disease
Single-cell RNA-seq · human · 21 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
- 21 samples: 21 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.
- Paper
- Revealing hyperactivated IFN-γ pathways in perianal fistulizing Crohn's disease using single-cell and spatial multi-omicsThe Journal of clinical investigation · 2025
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 GSE277387_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 PRJNA1162085 and SRA study SRP533275. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 21 sample titles: 21 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.
- GSM8521480 IPF1-scRNA
- GSM8521481 IPF4-scRNA
- GSM8521482 IPF5-scRNA
- GSM8521483 IPF6-scRNA
- GSM8521484 IPF7-scRNA
- GSM8521485 IPF8-scRNA
- GSM8521486 PCD1-scRNA
- GSM8521487 PCD2-scRNA
- GSM8521488 PCD3-scRNA
- GSM8521489 PCD4-scRNA
- GSM8521490 PCD5-scRNA
- GSM8521491 PCD6-scRNA
- GSM8521492 PCD7-scRNA
- GSM8521493 PCD8-scRNA
- GSM8521494 PCD9-scRNA
- GSM8521495 IPF1-ST
- GSM8521496 IPF2-ST
- GSM8521497 IPF3-ST
- GSM8521498 PCD1-ST
- GSM8521499 PCD2-ST
- GSM8521500 PCD3-ST
- GSE332623 Immunological Differences in Atopic Dermatitis Across Age Groups: Insights from Single-Cell Multi-Omics 54 samples shares single-cell, multi-omics
- GSE278694 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC 88 samples shares single-cell, spatial
- GSE283621 Single-cell multi-omics analysis identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastoma 79 samples shares single-cell, multi-omics
- GSE294559 Single-cell multi-omics characterize colorectal tumors, adjacent healthy tissue and matched organoids identifying CRC-unique features 72 samples shares single-cell, multi-omics
- GSE324131 A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis 38 samples shares single-cell, spatial
- GSE278688 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC [scRNA-Seq] 29 samples shares single-cell, spatial
- GSE176078 A single-cell and spatially resolved atlas of human breast cancers 26 samples shares single-cell, spatial
- GSE292623 A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma 18 samples shares single-cell, spatial
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.