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Multiomic profiling of pediatric solid organ transplant recipients and healthy children

GSE282427 Homo sapiens (human) Single-cell RNA-seq 100 samples Submitted 2025/12/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 100 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
Homo sapiens (human)
Samples
100 samples: 100 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
Multiomic Immune Profiling of Pediatric Transplant Recipients Identifies Cell States Associated with Vaccine ResponseClinical journal of the American Society of Nephrology : CJASN · 2026
Summary (written by the submitters)
PBMC of 12 pediatric solid organ transplant recipients (SOTR) and 8 healthy children (HC) were phenotyped using multiomic scRNAseq.
Published in
Multiomic Immune Profiling of Pediatric Transplant Recipients Identifies Cell States Associated with Vaccine Response
Wedel J, Tang Y, Alsairafi B et al. · Clinical journal of the American Society of Nephrology : CJASN 2026 · PMID 41442217 · doi:10.2215/CJN.0000000949
This dataset
Open GSE282427 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 GSE282427_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 PRJNA1187470. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41442217) ↗
Study design
100 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 100 sample titles: 100 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

+ 60 more — browse all 100 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.