Heterogeneous expression of cell surface markers in human myeloma cell lines: implications for disease modelling and therapeutic targeting
RNA-seq (gene expression) · human · 18 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
- 18 samples: 9 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.
- Paper
- Cell surface marker heterogeneity in human myeloma cell lines for modeling of disease and therapyScientific reports · 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 GSE250236_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 PRJNA1052711. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 18 samples.
How we read this: 9 replicated groups read from 18 sample titles; they account for 18 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.
- GSM7976037 ANBL6_R1 ANBL6
- GSM7976038 ANBL6_R2 ANBL6
- GSM7976039 IH1_R1 IH1
- GSM7976040 IH1_R2 IH1
- GSM7976041 INA6_R1 INA6
- GSM7976042 INA6_R2 INA6
- GSM7976043 JJN3_R1 JJN3
- GSM7976044 JJN3_R2 JJN3
- GSM7976045 KJON_R1 KJON
- GSM7976046 KJON_R2 KJON
- GSM7976047 OH2_R1 OH2
- GSM7976048 OH2_R2 OH2
- GSM7976049 URVIN_R1 URVIN
- GSM7976050 URVIN_R2 URVIN
- GSM7976051 VOLIN_R1 VOLIN
- GSM7976052 VOLIN_R2 VOLIN
- GSM7976053 FOLE_R1 FOLE
- GSM7976054 FOLE_R2 FOLE
- 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 myeloma
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares myeloma
- GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing · shares myeloma
- GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing · shares myeloma
- GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 4 samples same disease briefing · shares myeloma
- GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing · shares myeloma
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares myeloma
- GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing · shares 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.