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A Single-Cell Atlas of Transcriptional and Immunoglobulin Repertoire Evolution in Early B Cell Development

GSE337533 Homo sapiens (human) Single-cell RNA-seq 66 samples Submitted 2026/07/21 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 66 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
66 samples: 26 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)
The development of human B cells in the bone marrow can be separated into functionally and transcriptionally distinct subsets, which while canonically described have yet to be profiled deeply and individually and with NGS and bioinformatic techniques. In this study, single-cell RNA sequencing was performed on 65,110 B cells from six healthy donors to observe the foundation of the diversity observed in mature immune repertoires.
Read the full summary ↓
Following the established narrative of development, committed B cells undergo heavy and light chain recombination, which together form the functional BCR. However, a granular per-subset phenotypic analysis reveals proliferative bursts following each recombination event, an aspect of BCR recombination previously undescribed in the pro-B phase of development. Heavy and light chain pairing becomes more similar to that of mature, circulating B cells with progress through lymphopoiesis, deleting features associated with autoreactivity. Prominent among these repertoire alterations is a substantial shortening of heavy chain CDR3s, and changes in V, D, and J gene usage. This study provides a detailed snapshot of the transcriptomic and repertoire genetics landscape of developing B cells, providing a deeper understanding of the repertoire-shaping influence of early selection processes, and introducing new avenues for repertoire development research.
This dataset
Open GSE337533 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 GSE337533_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 PRJNA1490242 and SRA study SRP715305. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
26 conditions, mostly in duplicate
Gene expression library of Whole Bone Marrow … ×2 Gene expression library of Whole Bone Marrow … ×2 Gene expression library of Whole Bone Marrow … ×2 Gene expression library of B cell rxn 1 ×2 Gene expression library of B cell rxn 2 ×2 Gene expression library of B cell rxn 3 ×2 Gene expression library of B cell rxn 4 ×2 Gene expression library of CD34 positive rxn 3 ×2 +32 more

Supports a between-group comparison across 52 samples.

How we read this: 26 replicated groups read from 66 sample titles; they account for 52 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

+ 26 more — browse all 66 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.