A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [STARR-RNA-seq]
Single-nucleus RNA-seq · human · 16 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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
- 16 samples: 4 × NSC, histone, RNA, vs 4 × NSC, TF, RNA, vs 4 × ESC, histone, RNA, vs 4 × ESC, TF, RNA,Groups 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
- BRAIN-MAGNET: A functional genomics atlas for interpretation of non-coding variantsCell · 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 GSE263335_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 PRJNA1096726 and SRA study SRP500039. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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.
- GSM8189753 NSC, histone, RNA, rep1 NSC, histone, RNA,
- GSM8189754 NSC, histone, RNA, rep2 NSC, histone, RNA,
- GSM8189755 NSC, histone, RNA, rep3 NSC, histone, RNA,
- GSM8189756 NSC, histone, RNA, rep4 NSC, histone, RNA,
- GSM8189757 NSC, TF, RNA, rep1 NSC, TF, RNA,
- GSM8189758 NSC, TF, RNA, rep2 NSC, TF, RNA,
- GSM8189759 NSC, TF, RNA, rep3 NSC, TF, RNA,
- GSM8189760 NSC, TF, RNA, rep4 NSC, TF, RNA,
- GSM8189761 ESC, histone, RNA, rep1 ESC, histone, RNA,
- GSM8189762 ESC, histone, RNA, rep2 ESC, histone, RNA,
- GSM8189763 ESC, histone, RNA, rep3 ESC, histone, RNA,
- GSM8189764 ESC, histone, RNA, rep4 ESC, histone, RNA,
- GSM8189765 ESC, TF, RNA, rep1 ESC, TF, RNA,
- GSM8189766 ESC, TF, RNA, rep2 ESC, TF, RNA,
- GSM8189767 ESC, TF, RNA, rep3 ESC, TF, RNA,
- GSM8189768 ESC, TF, RNA, rep4 ESC, TF, RNA,
- GSE267549 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [wt RNA-seq] 2 samples shares interpretation, convolutional, facilitates, non-coding, regulatory, enhanced, networks
- GSE263337 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [ChIP-seq] 16 samples shares interpretation, convolutional, facilitates, non-coding, regulatory, enhanced, networks
- GSE263336 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [plasmid DNA-seq] 4 samples shares interpretation, convolutional, facilitates, non-coding, regulatory, enhanced, networks
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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.