A convenient single-cell newly synthesized transcriptome assay reveals FLI1 regulon downregulation during T-cell activation
Single-cell RNA-seq · human · 33 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
- 33 samples: 27 distinct titles, 3 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.
- Paper
- A convenient single-cell assay for the newly synthesized transcriptome reveals FLI1 regulon downregulation during T cell activationCell reports methods · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE270292_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1126143 and SRA study SRP516985. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 33 sample titles: 27 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.
- GSM8339158 no 4sU labeling, scRNA-seq
- GSM8339159 4sU labeling, scRNA-seq,eHAP
- GSM8339160 no 4sU labeling, scRNA-seq, SNP background for Jurkat
- GSM8339161 4sU labeling, scRNA-seq, unsti_J
- GSM8339162 4sU labeling, scRNA-seq, sti_J
- GSM8339163 no 4sU labeling, scRNA-seq, SNP background for mouse naïve T cell
- GSM8339164 4sU labeling, scRNA-seq, 0h
- GSM8339165 4sU labeling, scRNA-seq, 2h
- GSM8339166 4sU labeling, scRNA-seq, 4h
- GSM8339167 4sU labeling, scRNA-seq, 6h
- GSM8339168 4sU labeling, scRNA-seq, 8h
- GSM8339169 4sU labeling, control, rep1, SLAMseq
- GSM8339170 4sU labeling, control, rep2, SLAMseq
- GSM8339171 4sU labeling, 1mM, rep1, SLAMseq
- GSM8339172 4sU labeling, 1mM, rep2, SLAMseq
- GSM8339173 4sU labeling, 250µM, rep1, SLAMseq
- GSM8339174 4sU labeling, 250µM, rep2, SLAMseq
- GSM8339175 4sU labeling, 500µM, rep1, SLAMseq
- GSM8339176 4sU labeling, 500µM, rep2, SLAMseq
- GSM8676722 4sU labeling, control, rep1
- GSM8676723 4sU labeling, control, rep2
- GSM8676724 4sU labeling, control, rep3
- GSM8676725 4sU labeling, 50nM CPT, rep1
- GSM8676726 4sU labeling, 50nM CPT, rep2
- GSM8676727 4sU labeling, 50nM CPT, rep3
- GSM8676728 4sU labeling, 1µM ETO, rep1
- GSM8676729 4sU labeling, 1µM ETO, rep2
- GSM8676730 4sU labeling, 1µM ETO, rep3
- GSM9302159 4sU labeling, IAA, methanol, scRNA-seq
- GSM9302160 4sU labeling, no IAA, SNP background for K562, scRNA-seq
- GSM9302161 4sU labeling, IAA, scRNA-seq,
- GSM9302162 4sU labeling, scRNA-seq, unsti_J, rep1
- GSM9302163 4sU labeling, scRNA-seq, sti_J, rep1
- GSE285564 Single-cell transcriptome comparison of myeloid cells’ in the retina in response to transplantation of human stem-cell derived neurons and to ocular damage reveals the reversibility of the microglia activation. 3 samples shares single-cell, activation
- GSE44183 Genetic Programs in Human and Mouse Early Embryos Revealed by Single-Cell RNA-Sequencing 47 samples shares single-cell
- GSE242821 Atf3 controls transitioning in female mitochondrial cardiomyopathy as identified by single-cell transcriptomics 26 samples shares single-cell
- GSE300551 Massively multiplex multi-modal chemical screens at single-cell resolution with icCITE-plex 25 samples shares single-cell
- GSE268646 Functional phenotyping of genomic variants using joint multiomic single-cell DNA-RNA sequencing 17 samples shares single-cell
- GSE292322 HybriSeq: Probe-based Device-free Single-cell RNA Profiling 13 samples shares single-cell
- GSE223550 Secretion encoded single-cell sequencing (SEC-seq) uncovers gene expression signatures associated with high VEGF-A secretion in mesenchymal stromal cells 13 samples shares single-cell
- GSE299152 Single-cell mapping of the glycocalyx in the adult human and mouse ocular surface 12 samples shares single-cell
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.