Mucosal Single-Cell Profiling of Crohn's-Like Disease of the Pouch Reveals Unique Pathogenesis and Therapeutic Targets
Single-cell RNA-seq · human · 59 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
- 59 samples: 59 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
- Mucosal Single-Cell Profiling of Crohn's-Like Disease of the Pouch Reveals Unique Pathogenesis and Therapeutic TargetsGastroenterology · 2024
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 GSE246987_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 PRJNA1035495. 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 59 sample titles: 59 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.
- GSM7881808 pouch_ctrl1, scRNA-seq
- GSM7881809 ileum_ctrl1, scRNA-seq
- GSM7881810 pouch_ctrl2, scRNA-seq
- GSM7881811 ileum_ctrl2, scRNA-seq
- GSM7881812 pouch_ctrl3, scRNA-seq
- GSM7881813 ileum_ctrl3, scRNA-seq
- GSM7881814 pouch_ctrl4, scRNA-seq
- GSM7881815 ileum_ctrl4, scRNA-seq
- GSM7881816 pouch_ctrl5, scRNA-seq
- GSM7881817 ileum_ctrl5, scRNA-seq
- GSM7881818 pouch_cdp1, scRNA-seq
- GSM7881819 ileum_cdp1, scRNA-seq
- GSM7881820 pouch_cdp2, scRNA-seq
- GSM7881821 ileum_cdp2, scRNA-seq
- GSM7881822 pouch_cdp3, scRNA-seq
- GSM7881823 ileum_cdp3, scRNA-seq
- GSM7881824 pouch_cdp4, scRNA-seq
- GSM7881825 ileum_cdp4, scRNA-seq
- GSM7881826 pouch_cdp5, scRNA-seq
- GSM7881827 ileum_cdp5, scRNA-seq
- GSM7881828 pouch_cdp6, scRNA-seq
- GSM7881829 ileum_cdp6, scRNA-seq
- GSM7881830 pouch_ctrl1, scTCR-seq
- GSM7881831 ileum_ctrl2, scTCR-seq
- GSM7881832 pouch_ctrl3, scTCR-seq
- GSM7881833 ileum_ctrl3, scTCR-seq
- GSM7881834 pouch_ctrl4, scTCR-seq
- GSM7881835 ileum_ctrl4, scTCR-seq
- GSM7881836 pouch_ctrl5, scTCR-seq
- GSM7881837 ileum_ctrl5, scTCR-seq
- GSM7881838 pouch_cdp1, scTCR-seq
- GSM7881839 ileum_cdp1, scTCR-seq
- GSM7881840 pouch_cdp2, scTCR-seq
- GSM7881841 ileum_cdp2, scTCR-seq
- GSM7881842 pouch_cdp3, scTCR-seq
- GSM7881843 ileum_cdp3, scTCR-seq
- GSM7881844 pouch_cdp4, scTCR-seq
- GSM7881845 ileum_cdp4, scTCR-seq
- GSM7881846 pouch_cdp5, scTCR-seq
- GSM7881847 ileum_cdp5, scTCR-seq
+ 19 more — browse all 59 samples with per-sample file links →
- GSE233321 Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures 118 samples shares single-cell, unique
- GSE294559 Single-cell multi-omics characterize colorectal tumors, adjacent healthy tissue and matched organoids identifying CRC-unique features 72 samples shares single-cell, unique
- GSE300628 HER2 heterogeneous breast cancer models reveal novel therapeutic targets and subclonal dynamics during evolution to resistance to HER2-targeted therapies 60 samples shares therapeutic, targets
- GSE244832 Multi-Modal Comparison of human Hepatic Stellate Cells identifies novel therapeutic targets for Metabolic Dysfunction-Associated Steatotic Liver Disease 36 samples shares therapeutic, targets
- GSE199939 Comprehensive transcriptomic analysis of immune-related genes in diabetic foot ulcers: New insights into mechanisms and therapeutic targets 21 samples shares therapeutic, targets
- GSE285196 Pathogenesis of Graves' Disease Using Single-Cell Sequencing with Thyroid Autoantigens Peptides Stimulation in B Cells 10 samples shares pathogenesis, single-cell
- GSE279392 Single-cell RNA and TCR sequencing from skin, blood and cerebral spinal fluid (CSF) samples from Degos disease patients 116 samples shares single-cell
- GSE196198 Longitudinal single-cell multiomics data for different severity of COVID-19 100 samples shares single-cell
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.