Expression data of multiple myeloma patients at various stages of disease
RNA-seq (gene expression) · human · 23 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Multiple myelomaThis series is part of our curated briefing on it.
- Samples
- 23 samples: 15 × MM vs 8 × 9944Groups 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
- Individualized dynamic risk assessment and treatment selection for multiple myelomaBritish journal of cancer · 2025
Read the full summary ↓
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 GSE226176_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA939129 and SRA study SRP424732. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 23 samples.
How we read this: 2 replicated groups read from 23 sample titles; they account for 23 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.
- GSM7066487 9944-01 9944
- GSM7066488 9944-02 9944
- GSM7066489 9944-04 9944
- GSM7066490 9944-10 9944
- GSM7066491 9944-14 9944
- GSM7066492 9944-20 9944
- GSM7066493 9944-21 9944
- GSM7066494 9944-25 9944
- GSM7066495 MM137 MM
- GSM7066496 MM144 MM
- GSM7066497 MM154 MM
- GSM7066498 MM160 MM
- GSM7066499 MM173 MM
- GSM7066500 MM184 MM
- GSM7066501 MM194 MM
- GSM7066502 MM209 MM
- GSM7066503 MM26 MM
- GSM7066504 MM48 MM
- GSM7066505 MM59 MM
- GSM7066506 MM68 MM
- GSM7066507 MM80 MM
- GSM7066508 MM83 MM
- GSM7066509 MM84 MM
- 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
- 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
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 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
- GSE167968 RNA-seq of Multiple Myeloma 33 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
- GSE178328 Genome-wide maps of chromatin state in DEAF1 overexpression (OE in Multiple Myeloma) 2 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.