IRF4 requires ARID1A to establish plasma cell identity in multiple myeloma
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 99 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
- Multiple myelomaThis series is part of our curated briefing on it.
- Samples
- 99 samples: 46 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.
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 GSE253716_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 PRJNA1066800 and SRA study SRP484757. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 94 samples.
How we read this: 46 replicated groups read from 99 sample titles; they account for 94 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.
- GSM8026731 SKMM1 4 hours (ATAC2) DMSO 1 SKMM1 4 hours (ATAC2) D…
- GSM8026732 SKMM1 4 hours (ATAC2) DMSO 2 SKMM1 4 hours (ATAC2) D…
- GSM8026733 SKMM1 4 hours (ATAC2) FHD286 1 SKMM1 4 hours (ATAC2) F…
- GSM8026734 SKMM1 4 hours (ATAC2) FHD286 2 SKMM1 4 hours (ATAC2) F…
- GSM8026735 SKMM1 4 hours (ATAC2) Trametinib 1
- GSM8026736 SKMM1 4 hours (ATAC2) Tranetinib 2
- GSM8026737 SKMM1 4 hours (ATAC2) combination 1 SKMM1 4 hours (ATAC2) c…
- GSM8026738 SKMM1 4 hours (ATAC2) combination 2 SKMM1 4 hours (ATAC2) c…
- GSM8026739 NCIH929 4 hours (ATAC2) DMSO 1 NCIH929 4 hours (ATAC2)…
- GSM8026740 NCIH929 4 hours (ATAC2) DMSO 2 NCIH929 4 hours (ATAC2)…
- GSM8026741 NCIH929 4 hours (ATAC2) FHD286 1 NCIH929 4 hours (ATAC2)…
- GSM8026742 NCIH929 4 hours (ATAC2) FHD286 2 NCIH929 4 hours (ATAC2)…
- GSM8026743 NCIH929 4 hours (ATAC2) Trametinib 1
- GSM8026744 NCIH929 4 hours (ATAC2) Tranetinib 2
- GSM8026745 NCIH929 4 hours (ATAC2) combination 1 NCIH929 4 hours (ATAC2)…
- GSM8026746 NCIH929 4 hours (ATAC2) combination 2 NCIH929 4 hours (ATAC2)…
- GSM8026774 SKMM1 4 hours (ATAC1) DMSO 1 SKMM1 4 hours (ATAC1) D…
- GSM8026775 SKMM1 4 hours (ATAC1) DMSO 2 SKMM1 4 hours (ATAC1) D…
- GSM8026776 SKMM1 4 hours (ATAC1) AU15330 1 SKMM1 4 hours (ATAC1) A…
- GSM8026777 SKMM1 4 hours (ATAC1) AU15330 2 SKMM1 4 hours (ATAC1) A…
- GSM8026778 NCIH929 4 hours (ATAC1) DMSO 1 NCIH929 4 hours (ATAC1)…
- GSM8026779 NCIH929 4 hours (ATAC1) DMSO 2 NCIH929 4 hours (ATAC1)…
- GSM8026780 NCIH929 4 hours (ATAC1) AU15330 1 NCIH929 4 hours (ATAC1)…
- GSM8026781 NCIH929 4 hours (ATAC1) AU15330 2 NCIH929 4 hours (ATAC1)…
- GSM8026782 SKMM1 IRF4 1 SKMM1 IRF4
- GSM8026783 SKMM1 IRF4 2 SKMM1 IRF4
- GSM8026784 SKMM1 MYC 1 SKMM1 MYC
- GSM8026785 SKMM1 MYC 2 SKMM1 MYC
- GSM8026786 SKMM1 ARID1A 1 SKMM1 ARID1A
- GSM8026787 SKMM1 ARID1A 2 SKMM1 ARID1A
- GSM8026788 SKMM1 BRG1 1 SKMM1 BRG1
- GSM8026789 SKMM1 BRG1 2 SKMM1 BRG1
- GSM8026790 SKMM1 SMARCB1 1 SKMM1 SMARCB1
- GSM8026791 SKMM1 SMARCB1 2 SKMM1 SMARCB1
- GSM8026792 SKMM1 H3K4me3 1 SKMM1 H3K4me3
- GSM8026793 SKMM1 H3K4me3 2 SKMM1 H3K4me3
- GSM8026794 SKMM1 H3K27ac 1 SKMM1 H3K27ac
- GSM8026795 SKMM1 H3K27ac 2 SKMM1 H3K27ac
- GSM8026796 SKMM1 isotype control 1 SKMM1 isotype control
- GSM8026797 SKMM1 isotype control 2 SKMM1 isotype control
+ 59 more — browse all 99 samples with per-sample file links →
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 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
- 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
- GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 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.