scChIC-seq reveals focusing of global chromatin domains during differentiation
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 80 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
- 80 samples: 80 samples, each with a distinct title — no replicated groupsGroups 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.
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 GSE132266_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 PRJNA547348 and SRA study SRP200568. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 80 sample titles: 80 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.
- GSM3855270 B6_BM-H3K4me3-m1-2_H5VTLBGXB_S6
- GSM3855271 B6_BM-H3K4me3-m1-1_AH5WT3BGXB_S5
- GSM3855272 BM-H3K27me3-m1-2_AH3VGVBGX9_S2
- GSM3855273 B6_BM-H3K4me3-m1-4_AH5WT3BGXB_S8
- GSM3855274 B6_BM-H3K4me3-m1-2_AH5W5KBGXB_S6
- GSM3855275 B6_BM-H3K4me1-m1-4_AH5WT3BGXB_S4
- GSM3855276 K562-H3K9me3-G1-rep3_AH2GNLBGX9_S5
- GSM3855277 B6_BM-H3K27me3-m1-3_AH5WT3BGXB_S15
- GSM3855278 B6_BM-H3K4me1-m1-2_H5VTLBGXB_S2
- GSM3855279 BM-H3K4me1-m1-2_H2GV2BGX9_S11
- GSM3855280 B6_BM-H3K27me3-m1-1_AH5WT3BGXB_S13
- GSM3855281 BM-H3K27me3-m1-1_H2GV2BGX9_S14
- GSM3855282 K562-H3K9me3-G1-rep2_H2VTWBGX9_S9
- GSM3855283 B6_BM-H3K4me3-m1-2_AH5WT3BGXB_S6
- GSM3855284 B6_BM-H3K4me3-m1-3_AH5W5KBGXB_S7
- GSM3855285 K562-H3K4me1-G1-rep3_AH3T55BGX9_S1
- GSM3855286 B6_BM-H3K27me3-m1-1_AH5W5KBGXB_S13
- GSM3855287 BM-H3K4me3-m2-2_AH3VGVBGX9_S4
- GSM3855288 B6_BM-H3K4me3-m1-3_AH5WT3BGXB_S7
- GSM3855289 B6_BM-H3K4me1-m1-2_AH5WT3BGXB_S2
- GSM3855290 B6_BM-H3K27me3-m1-4_AH5W5KBGXB_S16
- GSM3855291 B6_BM-H3K9me3-m1-2_H5VTLBGXB_S10
- GSM3855292 B6_BM-H3K9me3-m1-1_AH5W5KBGXB_S9
- GSM3855293 B6_BM-H3K9me3-m1-4_AH5WT3BGXB_S12
- GSM3855294 B6_BM-H3K4me1-m1-1_AH5W5KBGXB_S1
- GSM3855295 B6_BM-H3K27me3-m1-3_H5VTLBGXB_S15
- GSM3855296 B6_BM-H3K27me3-m1-2_AH5W5KBGXB_S14
- GSM3855297 B6_BM-H3K4me3-m1-4_H5VTLBGXB_S8
- GSM3855298 K562-H3K4me1-G1-rep2_H2VTWBGX9_S6
- GSM3855299 B6_BM-H3K27me3-m1-3_AH5W5KBGXB_S15
- GSM3855300 B6_BM-H3K9me3-m1-2_AH5W5KBGXB_S10
- GSM3855301 B6_BM-H3K4me3-m1-1_H5VTLBGXB_S5
- GSM3855302 B6_BM-H3K4me1-m1-2_AH5W5KBGXB_S2
- GSM3855303 BM-H3K9me3-m2-2_AH3VGVBGX9_S5
- GSM3855304 B6_BM-H3K4me1-m1-3_H5VTLBGXB_S3
- GSM3855305 K562-H3K4me1-G1-rep1_H2VTWBGX9_S1
- GSM3855306 BM-H3K4me3-m1-2_H2GV2BGX9_S12
- GSM3855307 K562-H3K9me3-G1-rep3_AH3T55BGX9_S3
- GSM3855308 BM-H3K9me3-m1-1_H2GV2BGX9_S13
- GSM3855309 K562-H3K27me3-G1-rep1_H2VTWBGX9_S4
+ 40 more — browse all 80 samples with per-sample file links →
- GSE78109 Pathogenicity of genomic duplications is determined by formation of novel chromatin domains (neo-TADs) 48 samples shares chromatin, domains
- GSE66383 Disruptions of Topological Chromatin Domains Causes Pathogenic Rewiring of Gene-Enhancer Interactions 31 samples shares chromatin, domains
- GSE35156 Conserved Topological Domains in Mammalian Genomes Identified by High-resolution Analysis of Chromatin Interactions 9 samples shares chromatin, domains
- GSE65360 Single-cell chromatin accessibility data using scATAC-seq 1632 samples shares chromatin
- GSE269652 SP1 antagonizes H3K27me3 to shape chromatin landscapes for RNA polymerase II recruitment during gastrulation 106 samples shares chromatin
- GSE320163 Minimizing far-extending chromatin perturbation in genome editing preserves stem cell identity [ATAC-Seq] 377 samples shares chromatin
- GSE292571 SUMOylation orchestrates a metastable heterochromatin state on a MORC3-responsive element to silence IFNB1 at a distance [ChIP-seq] 116 samples shares chromatin
- GSE293172 Pioneer factors orchestrate tissue-specific cohesin-NIPBL chromatin entry and 3D genome organization [ChIP-seq] 68 samples shares 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.