Compendium of Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis [cutandrun]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 310 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Samples
- 310 samples: 79 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.
- Paper
- Disease-linked regulatory DNA variants and homeostatic transcription factors in epidermisNature 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 GSE255543_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1075324. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 255 samples.
How we read this: 79 replicated groups read from 310 sample titles; they account for 255 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.
- GSM8074177 AHR Prog 1 CnR 169 AHR Prog 1 Cn
- GSM8074178 AHR Prog 302
- GSM8074179 AHR Prog 1 CnR 435 AHR Prog 1 Cn
- GSM8074180 AHR Day4 1 CnR 161 AHR Day4 1 Cn
- GSM8074181 AHR Day4 282 AHR Day4
- GSM8074182 AHR Day4 299 AHR Day4
- GSM8074183 AHR Day4 1 CnR 411 AHR Day4 1 Cn
- GSM8074184 ATF4 Prog 1 CnR 90 ATF4 Prog 1 Cn
- GSM8074185 ATF4 Prog 2 CnR 91 ATF4 Prog 2 Cn
- GSM8074186 ATF4 Prog 1 CnR 333 ATF4 Prog 1 Cn
- GSM8074187 ATF4 Prog 2 CnR 334 ATF4 Prog 2 Cn
- GSM8074188 ATF4 Prog 1 CnR 433 ATF4 Prog 1 Cn
- GSM8074189 ATF4 Prog 2 CnR 434 ATF4 Prog 2 Cn
- GSM8074190 ATF4 Prog 1 CnR 458 ATF4 Prog 1 Cn
- GSM8074191 ATF4 Day4 1 CnR 109 ATF4 Day4 1 Cn
- GSM8074192 ATF4 Day4 2 CnR 110 ATF4 Day4 2 Cn
- GSM8074193 ATF4 Day4 1 CnR 365 ATF4 Day4 1 Cn
- GSM8074194 ATF4 Day4 2 CnR 366 ATF4 Day4 2 Cn
- GSM8074195 ATF4 Day4 1 CnR 409 ATF4 Day4 1 Cn
- GSM8074196 ATF4 Day4 2 CnR 410 ATF4 Day4 2 Cn
- GSM8074197 ATF4 Day4 3 CnR 500
- GSM8074198 CJUN Prog 1 CnR 138 CJUN Prog 1 Cn
- GSM8074199 CJUN Prog 1 CnR 180 CJUN Prog 1 Cn
- GSM8074200 CJUN Prog 1 CnR 349 CJUN Prog 1 Cn
- GSM8074201 CJUN Prog 2 CnR 350 CJUN Prog 2 Cn
- GSM8074202 CJUN Prog 1 CnR 415 CJUN Prog 1 Cn
- GSM8074203 CJUN Prog 2 CnR 416 CJUN Prog 2 Cn
- GSM8074204 CJUN Prog 1 CnR 442 CJUN Prog 1 Cn
- GSM8074205 CJUN Prog 2 CnR 443 CJUN Prog 2 Cn
- GSM8074206 CJUN Day4 1 CnR 146 CJUN Day4 1 Cn
- GSM8074207 CJUN Day4 1 CnR 196 CJUN Day4 1 Cn
- GSM8074208 CJUN Day4 1 CnR 381 CJUN Day4 1 Cn
- GSM8074209 CJUN Day4 2 CnR 382 CJUN Day4 2 Cn
- GSM8074210 CJUN Day4 1 CnR 399 CJUN Day4 1 Cn
- GSM8074211 CJUN Day4 2 CnR 400 CJUN Day4 2 Cn
- GSM8074212 CJUN Day4 1 CnR 474 CJUN Day4 1 Cn
- GSM8074213 CREB Prog 316
- GSM8074214 CREB Prog 1 CnR 439
- GSM8074215 CREB Day4 1 CnR 151 CREB Day4 1 Cn
- GSM8074216 CREB Day4 1 CnR 471 CREB Day4 1 Cn
+ 270 more — browse all 310 samples with per-sample file links →
- GSE302930 Epigenetic Atlas of Bladder Cancer Reveals Master Transcription Factors and Risk-Associated Regulatory Elements in Luminal and Basal-Squamous Molecular Subtypes 92 samples shares transcription, regulatory
- GSE182605 Integrative gene regulatory analysis reveals transcriptional mechanisms required in mature human hepatocytes and during in vitro hepatocyte differentiation 35 samples shares transcription, regulatory
- GSE284519 TRIM33 loss reduces Androgen Receptor transcriptional output and H2BK120 ubiquitination [ChIP-seq] 93 samples shares transcription
- GSE296190 Hypoxic regulation of chromatin and gene transcription [ChIP-seq] 84 samples shares transcription
- GSE335058 Evolutionary guided transcription factor design programs novel T cell states [ChIP-Seq] 66 samples shares transcription
- GSE293334 Allelic topological centering by transcription factors drives oncogenic multi-enhancer transcriptional regulation [ChIP-seq] 60 samples shares transcription
- GSE296831 Epigenetic Context Defines the Transcriptional Activity of Canonical and Noncanonical NF-kappaB Signaling in Pancreatic Cancer [ChIP-Seq] 48 samples shares transcription
- GSE294275 Transcriptional analysis of direct NSD2 target genes in t(4;14) multiple myeloma reveals H3K36me2-dependent regulation and H3K27me3 antagonism [CUT&TAG] 40 samples shares transcription
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.