Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 126 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 myeloid leukemiaThis series is part of our curated briefing on it.
- Samples
- 126 samples: 100 distinct titles, 13 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.
- Paper
- Functional characterization of cooperating MGA mutations in RUNX1::RUNX1T1 acute myeloid leukemiaLeukemia · 2024
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 GSE253753_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 PRJNA1066863 and SRA study SRP484783. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 126 sample titles: 100 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.
- GSM8027359 RNA-seq of Molm13 cells with homozygous deletion of MGA using CRISPR C2
- GSM8027360 RNA-seq of Molm13 cells with homozygous deletion of MGA using CRISPR C3
- GSM8027361 RNA-seq of Molm13 cells with homozygous deletion of MGA using CRISPR C4
- GSM8027362 RNA-seq of Molm13 cells with WT MGA C2
- GSM8027363 RNA-seq of Molm13 cells with WT MGA C3
- GSM8027364 RNA-seq of Molm13 cells with WT MGA C4
- GSM8027365 RNA-seq of cKit+ cells from Mga(+/+) C57/B6 mice #1
- GSM8027366 RNA-seq of cKit+ cells from Mga(+/+) C57/B6 mice #2
- GSM8027367 RNA-seq of cKit+ cells from Mga(+/+) C57/B6 mice #3
- GSM8027368 RNA-seq of cKit+ cells from Mga(+/+) C57/B6 mice #4
- GSM8027369 RNA-seq of cKit+ cells from Mga(+/-) C57/B6 mice #1
- GSM8027370 RNA-seq of cKit+ cells from Mga(+/-) C57/B6 mice #2
- GSM8027371 RNA-seq of cKit+ cells from Mga(+/-) C57/B6 mice #3
- GSM8027372 RNA-seq of cKit+ cells from Mga(+/-) C57/B6 mice #4
- GSM8027373 RNA-seq of cKit+ cells from Mga(-/-) C57/B6 mice #1
- GSM8027374 RNA-seq of cKit+ cells from Mga(-/-) C57/B6 mice #2
- GSM8027375 RNA-seq of cKit+ cells from Mga(-/-) C57/B6 mice #3
- GSM8027376 RNA-seq of cKit+ cells from Mga(-/-) C57/B6 mice #4
- GSM8027377 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/+) HSCs #1
- GSM8027378 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/+) HSCs #2
- GSM8027379 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/+) HSCs #3
- GSM8027380 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/-) HSCs #1
- GSM8027381 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/-) HSCs #2
- GSM8027382 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/-) HSCs #3
- GSM8027383 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(+/-) HSCs #4
- GSM8027384 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(-/-) HSCs #1
- GSM8027385 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(-/-) HSCs #2
- GSM8027386 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(-/-) HSCs #3
- GSM8027387 RNA-seq of RUNX1::RUNX1T1+ cells expressed in Mga(-/-) HSCs #4
- GSM8027391 2294319_SJAML075820_C1-MOLM13_WT-IGG-AB14
- GSM8027392 2294320_SJAML075820_C1-MOLM13_WT-MGA-AB1
- GSM8027393 2294321_SJAML075820_C1-MOLM13_WT-H3K4me3-AB12
- GSM8027394 2294322_SJAML075820_C1-MOLM13_WT-H3K27Ac-AB5
- GSM8027395 2294323_SJAML075820_C2-MOLM13_KO-MGA-AB1
- GSM8027396 2294324_SJAML075820_C2-MOLM13_KO-H3K4me3-AB12
- GSM8027397 2294325_SJAML075820_C2-MOLM13_KO-H3K27Ac-AB5
- GSM8027398 2348239_SJAML076231_C1-Molm13_WT-MGA-AB1
- GSM8027399 2348240_SJAML076231_C1-Molm13_WT-H2AK119ub1-AB1
- GSM8027400 2348241_SJAML076231_C1-Molm13_WT-H3K27me3-AB4
- GSM8027401 2348242_SJAML076231_C1-Molm13_WT-H3K4me3-AB12
+ 86 more — browse all 126 samples with per-sample file links →
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- GSE303795 Halofuginone exerts broad-spectrum cytotoxic effects by regulating p-eIF2α-S100A8/A9-calcium signaling, inhibiting global protein synthesis, and reversing the resistance of idarubicin in acute myeloid leukemia 6 samples same disease briefing · shares leukemia, myeloid, acute
- GSE129437 Genome-wde mapping of BRD9 binding sites and gene expression changes upon BRD9 knockdown 6 samples same disease briefing
- GSE122515 Bonn Dataset 3 of meta-analysis on AML classification, RNAseq dataset 0 samples same disease briefing
- GSE253750 Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia [Cut&Run] 87 samples shares runx1t1, runx1, mga, cooperating, mutations, leukemia, myeloid, acute
- GSE253748 Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia [RNA-seq] 29 samples shares runx1t1, runx1, mga, cooperating, mutations, leukemia, myeloid, acute
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.