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scRNA-seq and genomic reference of PBMC upon TNF Inhibitor Response in Ankylosing Spondylitis

GSE277117 Homo sapiens (human) Single-cell RNA-seq 62 samples Submitted 2025/05/02 Platform GPL21697Platform GPL28038
At a glance

Single-cell RNA-seq · human · 62 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
62 samples: 10 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.
Summary (written by the submitters)
To identify molecular factor that can predicts TNF inhibitor responsiveness for Ankylosing spondylitis patients. We performed scRNA-seq and CITE-seq before and after TNF or IL17 inhibitor treatment.
This dataset
Open GSE277117 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE277117_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1160823 and SRA study SRP532522. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in duplicate
PBMC, NR, WGS, KAS ×11 PBMC, R, TNFi, Pre, scRNA, KAS ×3 PBMC, R, WGS, KAS ×3 PBMC, NR, TNFi, Post, CITE, KAS ×2 PBMC, NR, TNFi, Post, scRNA, KAS ×2 PBMC, NR, TNFi, Pre, CITE, KAS ×2 PBMC, NR, TNFi, Pre, scRNA, KAS ×2 PBMC, NR, IL17i, Pre, CITE, KAS ×2 +33 more

Supports a between-group comparison across 31 samples.

How we read this: 10 replicated groups read from 62 sample titles; they account for 31 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.

Samples in this study

+ 22 more — browse all 62 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.