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A dual role for PSIP1/LEDGF in T-cell acute lymphoblastic leukemia

GSE253143 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 54 samples Submitted 2024/10/20 Platform GPL19057Platform GPL21273Platform GPL20795Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 54 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
Mus musculus (mouse)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
54 samples: 8 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
A dual role for PSIP1/LEDGF in T cell acute lymphoblastic leukemiaScience advances · 2024
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
A dual role for PSIP1/LEDGF in T cell acute lymphoblastic leukemia
Demoen L, Matthijssens F, Reunes L et al. · Science advances 2024 · PMID 39485844 · doi:10.1126/sciadv.ado6765
This dataset
Open GSE253143 in finder → Find more 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 GSE253143_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 PRJNA1064104 and SRA study SRP483396. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39485844) ↗
Study design
8 conditions, mostly in duplicate
Lck-Cre Pten Psip1 KO, thymoma, L ×9 Lck-Cre Pten Psip1 WT, thymoma, L ×6 CD2-iCre CD2-Lmo2 Psip1 WT, thymoma, CDNA ×6 CD2-iCre CD2-Lmo2 Psip1 KO, thymoma, CDNA ×6 CD2-iCre PSIP1 WT, H3K27me3, CUT&RUN, WT ×2 CD2-iCre PSIP1 WT, IgG, CUT&RUN, WT ×2 CD2-iCre PSIP1 KO, H3K27me3, CUT&RUN, KO ×2 CD2-iCre PSIP1 KO, IgG, CUT&RUN, KO ×2 +19 more

Supports a between-group comparison across 35 samples.

How we read this: 8 replicated groups read from 54 sample titles; they account for 35 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.

Samples in this study

+ 14 more — browse all 54 samples with per-sample file links →

More Acute lymphoblastic leukemia datasets

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

Share this dataset

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.