Comparison of transcriptional response in ZIKV-infected wildtype (B6J) and RIPK3 KO neurons
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.
- Paper
- RIPK3 coordinates RHIM domain-dependent antiviral inflammatory transcription in neuronsScience signaling · 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 GSE280963_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 PRJNA1181547 and SRA study SRP542842. 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.
- GSM8608006 B6J_Mock_1_24hrs
- GSM8608007 B6J_Mock_2_24hrs
- GSM8608008 B6J_Mock_3_24hrs
- GSM8608009 B6J_ZIKV_1_24hrs
- GSM8608010 B6J_ZIKV_2_24hrs
- GSM8608011 B6J_ZIKV_3_24hrs
- GSM8608012 RIPK3_Mock_1_24hrs
- GSM8608013 RIPK3_Mock_2_24hrs
- GSM8608014 RIPK3_Mock_3_24hrs
- GSM8608015 RIPK3_ZIKV_1_24hrs
- GSM8608016 RIPK3_ZIKV_2_24hrs
- GSM8608017 RIPK3_ZIKV_3_24hrs
- GSE280962 Idenitifying RIPK3 dependent genes in neurons expressing RIPK3-activatable system 18 samples shares ripk3, neurons
- GSE281959 Transcriptome comparison of RhoP23H/+ mouse retina with wildtype at different age 18 samples shares comparison, wildtype
- GSE281061 Assessing RIPK3 dependent genes in death-resistant and death-susceptible MEFs encoding activatable RIPK3-system 39 samples shares ripk3
- GSE281136 Assessing the role of RHIM proteins in RIPK3-transcription in MEFs 24 samples shares ripk3
- GSE264436 RIPK3 promotes neuronal survival by suppressing excitatory neurotransmission during CNS viral infection 18 samples shares ripk3
- GSE237891 Neuronal DAMPs exacerbate neurodegeneration via astrocytic RIPK3 signaling 13 samples shares ripk3
- GSE282452 Assessing the role of RIPK1 and TRIF proteins in RIPK3-transcription in MEFs 12 samples shares ripk3
- GSE305184 Dissection of kinase-dependent and independent functions of RIPK3 in inflammatory disease 12 samples shares ripk3
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.