Influence of GSK3 inhibition and beta Catenin stabilisation on the transcriptome of pre B cells
RNA-seq (gene expression) · mouse · 12 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
- Mus musculus (mouse)
- Samples
- 12 samples: 12 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 GSE179151_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 PRJNA742418 and SRA study SRP326156. 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 12 sample titles: 12 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.
- GSM5410646 #244 (KO)
- GSM5410647 #251 (WT)
- GSM5410648 #262 (ko)
- GSM5410649 #255 (ko)
- GSM5410650 #242 (WT)
- GSM5410651 #249 (WT)
- GSM5410652 #242-UT
- GSM5410653 #242-GSK3
- GSM5410654 #249-UT
- GSM5410655 #249-GSK3
- GSM5410656 #251-UT
- GSM5410657 #251-GSK3
- GSE245287 Beta-catenin deletion and GSK3b inhibition in B-ALL cells 12 samples shares gsk3, inhibition, catenin, beta
- GSE283254 AS1842856: A dual FOXO1-GSK3 inhibitor for targeting B-ALL-specific molecular vulnerabilities 24 samples shares gsk3
- GSE285231 Systems genetics reveals the influence of eQTLs in mouse embryonic stem cells on transcriptional variation later in differentiated neural progenitor cells 186 samples shares influence
- GSE318028 Pharmacological inhibition of FKBP51 mitigates early life adversity-induced social deficits 246 samples shares inhibition
- GSE337190 CAR-NKT cells induce low cytokine release syndrome by targeting hyperinflammatory macrophages with mitigation from GM-SCF inhibition. 24 samples shares inhibition
- GSE252926 Influence of GPR35 deficiency on the ileal and macrophage transcriptome 20 samples shares influence
- GSE293819 Monitoring systemic immune responses to checkpoint inhibition in breast cancer reveals host responses and mechanisms of resistance 142 samples shares inhibition
- GSE234105 Effect of OLIG2 inhibition on medulloblastoma stem cells 18 samples shares inhibition
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.