Tissue-Specific Determinants of Adaptive NK Cell Responses
RNA-seq (gene expression) · mouse · 54 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
- 54 samples: 54 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
- Splenic TNF-α signaling potentiates the innate-to-adaptive transition of antiviral NK cellsImmunity · 2025
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 GSE233352_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 PRJNA975925 and SRA study SRP439403. 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 54 sample titles: 54 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.
- GSM7426025 TNFR2KO,Ly49HposNK,d1,Spleen,2,11821
- GSM7426026 TNFR2KO,Ly49HposNK,d1,Spleen,4,11821
- GSM7426027 TNFR2KO,Ly49HposNK,d2,Spleen,2,11821
- GSM7426028 TNFR2KO,Ly49HposNK,d2,Spleen,3,11821
- GSM7426029 TNFR2KO,Ly49HposNK,d2,Spleen,4,11821
- GSM7426030 TNFR2KO,Ly49HposNK,d4,Spleen,2,11821
- GSM7426031 TNFR2KO,Ly49HposNK,d4,Spleen,3,11821
- GSM7426032 TNFR2KO,Ly49HposNK,d4,Spleen,4,11821
- GSM7426033 WT,Ly49HposNK,d1,Spleen,2,11821
- GSM7426034 WT,Ly49HposNK,d1,Spleen,4,11821
- GSM7426035 WT,Ly49HposNK,d2,Spleen,2,11821
- GSM7426036 WT,Ly49HposNK,d2,Spleen,3,11821
- GSM7426037 WT,Ly49HposNK,d2,Spleen,4,11821
- GSM7426038 WT,Ly49HposNK,d4,Spleen,2,11821
- GSM7426039 WT,Ly49HposNK,d4,Spleen,3,11821
- GSM7426040 WT,Ly49HposNK,d4,Spleen,4,11821
- GSM7426041 WT,RPMac,24h,Spleen,5,12080
- GSM7426042 WT,RPMac,24h,Spleen,6,12080
- GSM7426043 WT,RPMac,24h,Spleen,7,12080
- GSM7426044 WT,cDC1,24h,Spleen,1,12080
- GSM7426045 WT,cDC1,24h,Spleen,2,12080
- GSM7426046 WT,cDC1,24h,Spleen,3,12080
- GSM7426047 WT,pDC,24h,Spleen,5,12080
- GSM7426048 WT,pDC,24h,Spleen,6,12080
- GSM7426049 WT,pDC,24h,Spleen,7,12080
- GSM7426050 WT,RPMac,d0,Spleen,5,12080
- GSM7426051 WT,RPMac,d0,Spleen,6,12080
- GSM7426052 WT,RPMac,d0,Spleen,7,12080
- GSM7426053 WT,cDC1,d0,Spleen,1,12080
- GSM7426054 WT,cDC1,d0,Spleen,2,12080
- GSM7426055 WT,cDC1,d0,Spleen,3,12080
- GSM7426056 WT,pDC,d0,Spleen,5,12080
- GSM7426057 WT,pDC,d0,Spleen,6,12080
- GSM7426058 WT,pDC,d0,Spleen,7,12080
- GSM7426059 WT,RPMac,d2,Spleen,5,12080
- GSM7426060 WT,RPMac,d2,Spleen,7,12080
- GSM7426061 WT,RPMac,d2,Spleen,8,12080
- GSM7426062 WT,cDC1,d2,Spleen,1,12080
- GSM7426063 WT,cDC1,d2,Spleen,2,12080
- GSM7426064 WT,pDC,d2,Spleen,5,12080
+ 14 more — browse all 54 samples with per-sample file links →
- GSE233346 Tissue-Specific Determinants of Adaptive NK Cell Responses - Myeloid Cells 26 samples shares tissue-specific, determinants, adaptive
- GSE233345 Tissue-Specific Determinants of Adaptive NK Cell Responses - WT vs TNFR2ko NK 16 samples shares tissue-specific, determinants, adaptive
- GSE233347 Tissue-Specific Determinants of Adaptive NK Cell Responses - Spleen vs Liver NK 12 samples shares tissue-specific, determinants, adaptive
- GSE194200 Induction of transient and adaptive vs maladaptive unfolded protein responses of the endoplasmic reticulum in pancreatic beta cells 39 samples shares adaptive
- GSE294565 Inhibition of p53-MDM2 binding reduces senescent cell abundance and improves the adaptive responses of skeletal muscle from aged mice 32 samples shares adaptive
- GSE293097 Pre-existing allergic inflammation alters both innate and adaptive immune responses in mice co-infected with influenza virus 36 samples shares adaptive
- GSE303515 Sequential adaptive changes in a c-Myc-driven model of hepatocellular carcinoma 34 samples shares adaptive
- GSE190035 Characterisation of the epidermal diurnal and circadian transcriptomes of mice with tissue-specific circadian clock activity 216 samples shares tissue-specific
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.