Bulk RNA-seq after Overexpression of EFNB2 in U266 Multiple Myeloma Cells
RNA-seq (gene expression) · human · 10 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
- 10 samples: 10 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 GSE256290_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 PRJNA1078873 and SRA study SRP490863. 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 10 sample titles: 10 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.
- GSM8093085 U266_gRNA2_Sample_A_S1
- GSM8093086 U266_gRNA2_Sample_B_S2
- GSM8093087 U266_gRNA2_Sample_C_S3
- GSM8093088 U266_gRNA2_Sample_D_S4
- GSM8093089 U266_gRNA2_Sample_E_S5
- GSM8093090 U266_cgRNA_Sample_A_S6
- GSM8093091 U266_cgRNA_Sample_B_S7
- GSM8093092 U266_cgRNA_Sample_C_S8
- GSM8093093 U266_cgRNA_Sample_D_S9
- GSM8093094 U266_cgRNA_Sample_E_S10
- 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, rna-seq, myeloma
- GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing · shares multiple, rna-seq, myeloma
- GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 4 samples same disease briefing · shares overexpression, multiple, myeloma
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares multiple, rna-seq, myeloma
- GSE178328 Genome-wide maps of chromatin state in DEAF1 overexpression (OE in Multiple Myeloma) 2 samples same disease briefing · shares overexpression, multiple, myeloma
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 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
- GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 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.