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Repertoire FLEX (REFLEX) Enables High-Throughput Multiomic scRNAseq with AIR Detection

GSE314863 Homo sapiens (human) Single-cell RNA-seq 127 samples Submitted 2026/06/30 Platform GPL30173Platform GPL34281
At a glance

Single-cell RNA-seq · human · 127 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
127 samples: 109 distinct titles, 16 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)
Profiling the vast diversity of the T-cell repertoire at single-cell resolution is challenging due to the scale and cost requirements involved. Current technologies capture TCR or perform single-cell sequencing at scale but struggle to combine both. Here, we utilize both neat and virally stimulated PBMCs to showcase “REFLEX”, a technological approach enabling highly scalable, low cost-per-cell profiling of TCR repertoire in parallel with epitope and gene expression.
Read the full summary ↓
This combination of capabilities allows for high throughput, multi-omic profiling of rare T cell subsets and longitudinal study formats at scales that were previously unattainable.
This dataset
Open GSE314863 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 GSE314863_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 PRJNA1377320 and SRA study SRP653228. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
109 distinct titles, 16 of them repeated
Long-Bridge RT Probe Test BC ×16 Jurkat BC ×2 Raji BC ×2 Jurkat/Raji BC ×2 (KT10434) BW3446Std +pep ×2 (KT10434) BW3446Std -pep ×2 (KT10435) BW2164Std +pep ×2 (KT10435) BW2164Std -pep ×2 +8 more

How we read this: Read from 139 sample titles: 109 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

+ 87 more — browse all 127 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.