Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [RNA-seq]
RNA-seq (gene expression) · human · 3 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 3 samples
- 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
- Dissecting regulatory non-coding GWAS loci reveals fibroblast causal genes with pathophysiological relevance to heart failureNature communications · 2025
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 GSE281465_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1183890 and SRA study SRP544097. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 3 more — browse all 3 samples with per-sample file links →
- GSE281464 Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Perturb-seq] 7 samples shares gwas, high-resolution, interactions, dissecting, non-coding, chromatin, relevance, failure
- GSE293119 Integration of Alzheimer’s GWAS, 3D genomics, and single-cell CRISPRi non-coding screen implicates causal variants in a microglial enhancer regulating TSPAN14. [RNA-Seq] 18 samples shares gwas, non-coding
- GSE293846 Identification of known and novel long non-coding RNAs potentially responsible for the effects of BMD GWAS loci [hFOB RNA-seq] 18 samples shares gwas, non-coding
- GSE263804 Chromatin accessibility mapping for functional GWAS risk variants of neuropsychiatric and neurodegenerative disorders in hiPSC-derived neural cells 141 samples shares gwas, chromatin
- GSE216549 Central role of SUMOylation in the regulation of chromatin interactions and transcriptional outputs of androgen receptor in prostate cancer cells (LNCaP RNA-seq) 24 samples shares interactions, chromatin
- GSE263641 CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation. 137 samples shares interactions, chromatin
- GSE211164 Central role of SUMOylation in the regulation of chromatin interactions and transcriptional outputs of androgen receptor in prostate cancer cells 64 samples shares interactions, chromatin
- GSE310006 The NuRD chromatin remodeling complex regulates tRNA genes through direct interactions with RNA polymerase III 54 samples shares interactions, chromatin
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.