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Genome-wide maps of chromatin state for histone modifications and chromatin remodeling factors in WT and PHF6-KO conditions in Jurkat T-ALL cells.

GSE193713 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2025/01/13 Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
20 samples: 18 distinct titles, 2 of them repeatedGroups 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.
Summary (written by the submitters)
We have carried out high-throughput profiling of histone modifications and transcription factors in mammalian cells. First we generated stable PHF6 knock out lines by CRISPR-Cas9 technology in wild type Jurkat cells. We electroporated the RNP complex in Jurkat cells conatining guide RNAs against either non-targeting (EV) or PHF6 (KO) followed by single clone isolation and expansion.
Read the full summary ↓
We confirmed absolute loss of total protein by WB and indel formation (mutation efficiency) at the PHF6 genomic locus by Sanger sequencing. By obtaining over six to ten billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of well studied histone modifications and transcription factors. This study provides a framework for eluciadting the role of PHF6 in regulating the chromatin landscape encompassing both activating and repressive histone modifications and chromatin remodelers in the context of leukemia.
This dataset
Open GSE193713 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Acute lymphoblastic leukemia landscape →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE193713_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA797372 and SRA study SRP355832. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 distinct titles, 2 of them repeated
PHF6-WT_CHD4_L ×2 PHF6-KO_CHD4_L ×2

How we read this: Read from 20 sample titles: 18 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.

Samples in this study
More Acute lymphoblastic leukemia datasets

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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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.