Transient promoter interactions modulate developmental gene activation [RNA-Seq]
RNA-seq (gene expression) · mouse · 79 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
- 79 samples: 79 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.
- Paper
- Transient promoter interactions modulate developmental gene activationMolecular cell · 2024
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 GSE261066_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 PRJNA1085204 and SRA study SRP493822. 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 79 sample titles: 79 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.
- GSM8133527 SCC1.AID_IAA.RA_rep1_cnucRNAseq
- GSM8133528 SCC1.AID_IAA.RA_rep2_cnucRNAseq
- GSM8133529 SCC1.AID_IAA.RA_rep3_cnucRNAseq
- GSM8133530 SCC1.AID_IAA_rep1_cnucRNAseq
- GSM8133531 SCC1.AID_IAA_rep2_cnucRNAseq
- GSM8133532 SCC1.AID_IAA_rep3_cnucRNAseq
- GSM8133533 SCC1.AID_RA_rep1_cnucRNAseq
- GSM8133534 SCC1.AID_RA_rep2_cnucRNAseq
- GSM8133535 SCC1.AID_RA_rep3_cnucRNAseq
- GSM8133536 SCC1.AID_UNT_rep1_cnucRNAseq
- GSM8133537 SCC1.AID_UNT_rep2_cnucRNAseq
- GSM8133538 SCC1.AID_UNT_rep3_cnucRNAseq
- GSM8133539 HoxTransE_KO_CE3_RA0h_rep1_nucRNAseq
- GSM8133540 HoxTransE_KO_CE3_RA2h_rep1_nucRNAseq
- GSM8133541 HoxTransE_KO_CE3_RA4h_rep1_nucRNAseq
- GSM8133542 HoxTransE_KO_CE3_RA6h_rep1_nucRNAseq
- GSM8133543 HoxTransE_KO_CE3_RA24h_rep1_nucRNAseq
- GSM8133544 HoxTransE_KO_CE3_RA48h_rep1_nucRNAseq
- GSM8133545 HoxTransE_KO_CE3_RA74h_rep1_nucRNAseq
- GSM8133546 HoxTransE_KO_CE3_RA0h_rep2_nucRNAseq
- GSM8133547 HoxTransE_KO_CE3_RA2h_rep2_nucRNAseq
- GSM8133548 HoxTransE_KO_CE3_RA4h_rep2_nucRNAseq
- GSM8133549 HoxTransE_KO_CE3_RA6h_rep2_nucRNAseq
- GSM8133550 HoxTransE_KO_CE3_RA24h_rep2_nucRNAseq
- GSM8133551 HoxTransE_KO_CE3_RA48h_rep2_nucRNAseq
- GSM8133552 HoxTransE_KO_CE3_RA74h_rep2_nucRNAseq
- GSM8133553 HoxTransE_WT_CG4_RA0h_rep1_nucRNAseq
- GSM8133554 HoxTransE_WT_CG4_RA2h_rep1_nucRNAseq
- GSM8133555 HoxTransE_WT_CG4_RA4h_rep1_nucRNAseq
- GSM8133556 HoxTransE_WT_CG4_RA6h_rep1_nucRNAseq
- GSM8133557 HoxTransE_WT_CG4_RA24h_rep1_nucRNAseq
- GSM8133558 HoxTransE_WT_CG4_RA48h_rep1_nucRNAseq
- GSM8133559 HoxTransE_WT_CG4_RA74h_rep1_nucRNAseq
- GSM8133560 HoxTransE_WT_CG4_RA0h_rep2_nucRNAseq
- GSM8133561 HoxTransE_WT_CG4_RA2h_rep2_nucRNAseq
- GSM8133562 HoxTransE_WT_CG4_RA4h_rep2_nucRNAseq
- GSM8133563 HoxTransE_WT_CG4_RA6h_rep2_nucRNAseq
- GSM8133564 HoxTransE_WT_CG4_RA24h_rep2_nucRNAseq
- GSM8133565 HoxTransE_WT_CG4_RA48h_rep2_nucRNAseq
- GSM8133566 HoxTransE_WT_CG4_RA74h_rep2_nucRNAseq
+ 39 more — browse all 79 samples with per-sample file links →
- GSE243942 Spatio-temporal X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing [RNA-seq] 125 samples shares activation, rna-seq
- GSE275510 Deciphering Motor Dysfunction and Microglial Activation in mThy1-α-Synuclein Mice: A Comprehensive Study of Behavioral, Gene Experssion, and Methylation Changes [RNA-Seq] 20 samples shares activation, rna-seq
- GSE295196 m6A RNA methylation in the maintenance of X-chromosome inactivation and X to autosome dosage compensation in early embryogenesis [RNA-Seq] 14 samples shares activation, rna-seq
- GSE296993 H3K9 di-methylation dynamics underlies mouse minor zygotic genome activation [RNA-seq of mESC] 50 samples shares activation, rna-seq
- GSE281467 Coactivation of innate immune suppressive cells induces acquired resistance against cancer immunotherapy targeting the innate immune system [TIICs RNA-seq] 30 samples shares activation, rna-seq
- GSE245648 The Heme-regulated transcriptional repressor, BACH1 safeguards macrophage enhancer selection, activation andtissue adaptation [RNA-seq_BMDM] 24 samples shares activation, rna-seq
- GSE313021 STING–IFN–CH25H lipid axis links innate immune activation to tau pathology [scRNA-seq] 16 samples shares activation, rna-seq
- GSE293372 Coordinate tumor-antigen uptake and dendritic cell activation by chimeric antigen receptors. [RNA-seq] 12 samples shares activation, rna-seq
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.