Regulation of IkB kinase family crosstalk by an N4BP1-caspase-8 axis [RNA-seq NGS3799]
RNA-seq (gene expression) · mouse · 36 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
- 36 samples: 36 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
- N4BP1 coordinates ubiquitin-dependent crosstalk within the IκB kinase family to limit Toll-like receptor signaling and inflammationImmunity · 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 GSE218956_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 PRJNA906451 and SRA study SRP410385. 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 36 sample titles: 36 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.
- GSM6760802 KO +R837 7h [SAM24402129]
- GSM6760803 KO +R837 7h [SAM24402128]
- GSM6760804 KO +R837 7h [SAM24402127]
- GSM6760805 WT +R837 7h [SAM24402126]
- GSM6760806 WT +R837 7h [SAM24402125]
- GSM6760807 WT +R837 7h [SAM24402124]
- GSM6760808 KO +R837 3h +ActD 4h [SAM24402123]
- GSM6760809 KO +R837 3h +ActD 4h [SAM24402122]
- GSM6760810 KO +R837 3h +ActD 4h [SAM24402121]
- GSM6760811 WT +R837 3h +ActD 4h [SAM24402120]
- GSM6760812 WT +R837 3h +ActD 4h [SAM24402119]
- GSM6760813 WT +R837 3h +ActD 4h [SAM24402118]
- GSM6760814 KO +R837 3h +ActD 2h [SAM24402117]
- GSM6760815 KO +R837 3h +ActD 2h [SAM24402116]
- GSM6760816 KO +R837 3h +ActD 2h [SAM24402115]
- GSM6760817 WT +R837 3h +ActD 2h [SAM24402114]
- GSM6760818 WT +R837 3h +ActD 2h [SAM24402113]
- GSM6760819 WT +R837 3h +ActD 2h [SAM24402112]
- GSM6760820 KO +R837 3h +ActD 1h [SAM24402111]
- GSM6760821 KO +R837 3h +ActD 1h [SAM24402110]
- GSM6760822 KO +R837 3h +ActD 1h [SAM24402109]
- GSM6760823 WT +R837 3h +ActD 1h [SAM24402108]
- GSM6760824 WT +R837 3h +ActD 1h [SAM24402107]
- GSM6760825 WT +R837 3h +ActD 1h [SAM24402106]
- GSM6760826 KO +R837 3h +ActD 0.5h [SAM24402105]
- GSM6760827 KO +R837 3h +ActD 0.5h [SAM24402104]
- GSM6760828 KO +R837 3h +ActD 0.5h [SAM24402103]
- GSM6760829 WT +R837 3h +ActD 0.5h [SAM24402102]
- GSM6760830 WT +R837 3h +ActD 0.5h [SAM24402101]
- GSM6760831 WT +R837 3h +ActD 0.5h [SAM24402100]
- GSM6760832 KO +R837 3h [SAM24402099]
- GSM6760833 KO +R837 3h [SAM24402098]
- GSM6760834 KO +R837 3h [SAM24402097]
- GSM6760835 WT +R837 3h [SAM24402096]
- GSM6760836 WT +R837 3h [SAM24402095]
- GSM6760837 WT +R837 3h [SAM24402094]
- GSE327205 RNA-seq analysis of dorsal root ganglia (DRG) from MIA-induced osteoarthritis mice with acupuncture or no treatment: Focus on neuro-immune crosstalk genes 8 samples shares crosstalk, rna-seq
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares rna-seq
- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples shares rna-seq
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares rna-seq
- GSE319614 Bulk RNA-seq transcriptome profiling of hippocampus across 17 autism spectrum disorder mouse models 269 samples shares rna-seq
- GSE304862 Semaglutide and exercise synergy in obesity: preserving muscle mass and uncovering organ crosstalk 209 samples shares crosstalk
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 samples shares rna-seq
- GSE98969 Single cell RNA-seq identifies a unique microglia type associated with Alzheimer’s disease [RNA] 97 samples shares 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.