DNase-seq from K562 (ENCSR335RHJ)
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 26 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
- 26 samples: 26 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.
- Paper
- An integrated encyclopedia of DNA elements in the human genomeNature · 2012
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 GSE322895_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 PRJNA63443 and SRA study SRP000592. 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 26 sample titles: 26 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.
- GSM9560621 DNase-seq from K562 (ENCLB561MWW)
- GSM9560622 DNase-seq from K562 (ENCLB880UOW)
- GSM9560623 DNase-seq from K562 (ENCLB504RZW)
- GSM9560624 DNase-seq from K562 (ENCLB105SIJ)
- GSM9560625 DNase-seq from K562 (ENCLB963CGW)
- GSM9560626 DNase-seq from K562 (ENCLB670TIP)
- GSM9560627 DNase-seq from K562 (ENCLB999FYU)
- GSM9560628 DNase-seq from K562 (ENCLB193XCE)
- GSM9560629 DNase-seq from K562 (ENCLB998ITK)
- GSM9560630 DNase-seq from K562 (ENCLB784NIK)
- GSM9560631 DNase-seq from K562 (ENCLB051EMW)
- GSM9560632 DNase-seq from K562 (ENCLB295BYB)
- GSM9560633 DNase-seq from K562 (ENCLB001YFG)
- GSM9560634 DNase-seq from K562 (ENCLB924URO)
- GSM9560635 DNase-seq from K562 (ENCLB056KKK)
- GSM9560636 DNase-seq from K562 (ENCLB714ARI)
- GSM9560637 DNase-seq from K562 (ENCLB465AWD)
- GSM9560638 DNase-seq from K562 (ENCLB751VMS)
- GSM9560639 DNase-seq from K562 (ENCLB421YWV)
- GSM9560640 DNase-seq from K562 (ENCLB746WOK)
- GSM9560641 DNase-seq from K562 (ENCLB929AYM)
- GSM9560642 DNase-seq from K562 (ENCLB734HZU)
- GSM9560643 DNase-seq from K562 (ENCLB787ASX)
- GSM9560644 DNase-seq from K562 (ENCLB902VHC)
- GSM9560645 DNase-seq from K562 (ENCLB408ZUQ)
- GSM9560646 DNase-seq from K562 (ENCLB063XDO)
- GSE320979 DNase-seq from K562 (ENCSR160FPV) 134 samples shares k562, dnase-seq
- GSE321204 DNase-seq from K562 (ENCSR736XRU) 9 samples shares k562, dnase-seq
- GSE322942 DNase-seq from K562 (ENCSR840YOF) 9 samples shares k562, dnase-seq
- GSE321771 DNase-seq from K562 (ENCSR425QOB) 7 samples shares k562, dnase-seq
- GSE99172 Single-cell chromatin accessibility data from K562 cells using scATAC-seq 288 samples shares k562
- GSE276857 CUT&Tag in K562, HCT116, RPE1 and Jurkat cells 39 samples shares k562
- GSE246552 Profiling R loop in mouse and human hematopietic cells with low cell input using S9.6 antibody coupled cut&tag [cut&tag K562] 30 samples shares k562
- GSE261411 BPDCN MYB Fusions Regulate Cell Cycle Genes, Impair Differentiation and Induce Myeloid-Dendritic Cell Leukemia [K562CutRun] 20 samples shares k562
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.