Identifying STRN3-RARA as a new fusion gene for acute promyelocytic leukemia
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 22 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 myeloid leukemiaThis series is part of our curated briefing on it.
- Samples
- 22 samples: 8 conditions, mostly in triplicateGroups 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
- Identifying STRN3-RARA as a new fusion gene for acute promyelocytic leukemiaBlood · 2023
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 GSE224816_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 PRJNA932745 and SRA study SRP424212. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 20 samples.
How we read this: 8 replicated groups read from 22 sample titles; they account for 20 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.
- GSM7033522 CUTTAG_IgG-1 CUTTAG_IgG
- GSM7033523 CUTTAG_IgG-2 CUTTAG_IgG
- GSM7033524 CUTTAG_SR-1 CUTTAG_S
- GSM7033525 CUTTAG_SR-2 CUTTAG_S
- GSM7033533 RNAseq_pMIG-1 RNAseq_pMIG
- GSM7033534 RNAseq_pMIG-2 RNAseq_pMIG
- GSM7033535 RNAseq_pMIG-3 RNAseq_pMIG
- GSM7033536 RNAseq_sgUTX-pMIG-1 RNAseq_sgUTX-pMIG
- GSM7033537 RNAseq_sgUTX-pMIG-2 RNAseq_sgUTX-pMIG
- GSM7033538 RNAseq_sgUTX-pMIG-3 RNAseq_sgUTX-pMIG
- GSM7033539 RNAseq_sgUTX-SR-1 RNAseq_sgUTX-S
- GSM7033540 RNAseq_sgUTX-SR-2 RNAseq_sgUTX-S
- GSM7033541 RNAseq_sgUTX-SR-3 RNAseq_sgUTX-S
- GSM7033542 RNAseq_SR-1 RNAseq_S
- GSM7033543 RNAseq_SR-2 RNAseq_S
- GSM7033544 RNAseq_SR-3 RNAseq_S
- GSM7663521 RNAseq_WCH01_pretreat
- GSM7663522 RNAseq_WCH01_relapse
- GSM7663523 RNAseq_Mouse_SR_ATRA_1 RNAseq_Mouse_SR_ATRA
- GSM7663524 RNAseq_Mouse_SR_ATRA_2 RNAseq_Mouse_SR_ATRA
- GSM7663525 RNAseq_Mouse_SR_Veh_1 RNAseq_Mouse_SR_Veh
- GSM7663526 RNAseq_Mouse_SR_Veh_2 RNAseq_Mouse_SR_Veh
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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.