GEO series

Longitudinal CITE-seq analysis in juvenile-onset systemic sclerosis monocytes following autologous stem cell transplant

GSE332819 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2026/07/30 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 15 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: 15 samples: 12 distinct titles, 1 of them repeatedGroups 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)

Juvenile systemic sclerosis (jSSc) is a rare and severe autoimmune disease marked by skin fibrosis and damage to multiple organ systems. This study implements autologous stem cell transplantation (ASCT), a newly available treatment protocol which aims to restore immune homeostasis, in this case amongst jSSc patients. Here, we analyze peripheral blood mononuclear cells (PBMCs) from 3 jSSc patients prior to ASCT and 6, 12, and 24 months post treatment.

Read the full summary ↓

These samples were then sequenced and tagged with antibodies using cellular indexing of transcriptomes and epitopes (CITE-seq). To analyze these samples and how they change over time, this study implements a newly designed generalized linear model. It was adopted from an established method with a coefficient for time since ASCT to identify numerous genes and pathways with downward longitudinal trends, many of which have previously been implicated in SSc development, and may help further understand disease pathogenesis. Our longitudinal differential gene expression analysis focused mainly on monocytes, which demonstrated strong downwards trends in multiple pathogenic genes/pathways. Specifically, nuclear factor-B (NFB)-driven inflammatory signaling was increased in jSSc monocytes at baseline compared to healthy controls, but decreased to match healthy monocyte levels over time following ASCT. We also note a sharp longitudinal reduction in jSSc monocyte expression of SERPINE1, a gene which has previously been implicated in SSc pathogenesis.This workflow describes immune reprogramming in three jSSc patients who underwent ASCT and introduces a statistically-justified framework for longitudinal single-cell modeling.

This dataset

Open GSE332819 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 GSE332819_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 PRJNA1469133 and SRA study SRP702706. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 distinct titles, 1 of them repeated

Healthy control ×4

How we read this: Read from 15 sample titles: 12 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.

Samples in this study

GSM9753927 Sample 515, 24 months post ASCT
GSM9753928 Sample 515, 6 months post ASCT
GSM9753929 Sample 515, pre -ASCT
GSM9753930 Sample 591, 12 months post ASCT
GSM9753931 Sample 591, 24 months post ASCT
GSM9753932 Sample 591, 6 months post ASCT
GSM9753933 Sample 591, pre-ASCT
GSM9753934 Sample 594, 12 months post ASCT
GSM9753935 Sample 594, 24 months post ASCT
GSM9753936 Sample 594, 6 months post ASCT
GSM9753937 Sample 594, pre-ASCT
GSM9753938 Healthy control 1
GSM9753939 Healthy control 2
GSM9753940 Healthy control 3
GSM9753941 Healthy control 4

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