KDM6A Regulates Immunogenicity of Multiple Myeloma (ChIP-seq)
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 24 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
- Multiple myelomaThis series is part of our curated briefing on it.
- Samples
- 24 samples: 24 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.
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 GSE244510_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 PRJNA1023291 and SRA study SRP464256. 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 24 sample titles: 24 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.
- GSM7818413 input-ARP1-KDM6A-H1146E
- GSM7818414 input-ARP1-KDM6A-KO
- GSM7818415 input-ARP1-KDM6A-WT
- GSM7818416 K27ac-ARP1-KDM6A-H1146E
- GSM7818417 K27ac-ARP1-KDM6A-KO
- GSM7818418 K27ac-ARP1-KDM6A-WT
- GSM7818419 K27me3-ARP1-KDM6A-H1146E
- GSM7818420 K27me3-ARP1-KDM6A-KO
- GSM7818421 K27me3-ARP1-KDM6A-WT
- GSM7818422 K4me1ARP-1E4
- GSM7818423 K4me1ARP-1WT
- GSM7818424 K27ac-MEF-KDM6A-KO
- GSM7818425 K27ac-MEF-KDM6A-KO-KRAS
- GSM7818426 K27ac-MEF-KDM6A-WT
- GSM7818427 K27ac-MEF-KDM6A-WT-KRAS
- GSM7818428 K27me3-MEF-KDM6A-KO
- GSM7818429 K27me3-MEF-KDM6A-KO-KRAS
- GSM7818430 K27me3-MEF-KDM6A-WT
- GSM7818431 K27me3-MEF-KDM6A-WT-KRAS
- GSM7818432 HA-IP-ARP1-KDM6A
- GSM7818433 HA-IP-ARP1-KDM6A-HAtagged
- GSM7818434 KDM6A-IP-ARP1-KDM6A-KO
- GSM7818435 KDM6A-IP-ARP1-KDM6A-WT
- GSM7818436 KDM6A-IP-KARPAS-KDM6A-WT
- GSE178328 Genome-wide maps of chromatin state in DEAF1 overexpression (OE in Multiple Myeloma) 2 samples same disease briefing · shares multiple, myeloma
- GSE161195 Single cell RNA-seq of relapsed and refractory multiple myeloma patients defines new resistance pathways and targeted treatments 213 samples same disease briefing · shares multiple, myeloma
- GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing · shares multiple, myeloma
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares multiple, myeloma
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares multiple, myeloma
- GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing · shares multiple, myeloma
- GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing · shares multiple, myeloma
- GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing · shares multiple, myeloma
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.