The GPR84 molecule is a mediator of a subpopulation of retinal microglia that promote TNF/IL-1α expression via the rho-ROCK pathway after optic nerve injury II
RNA-seq (gene expression) · mouse · 144 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
- 144 samples: 30 conditions, mostly with about 6 replicates eachGroups 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
- The GPR84 molecule is a mediator of a subpopulation of retinal microglia that promote TNF/IL-1α expression via the rho-ROCK pathway after optic nerve injuryGlia · 2023
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 GSE232746_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 PRJNA973685 and SRA study SRP438257. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 144 samples.
How we read this: 30 replicated groups read from 144 sample titles; they account for 144 of them. 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.
- GSM7373161 PBS_Plate1.A1 PBS_Plate1.A
- GSM7373162 PBS_Plate1.A2 PBS_Plate1.A
- GSM7373163 PBS_Plate1.A3 PBS_Plate1.A
- GSM7373164 PBS_Plate1.A4 PBS_Plate1.A
- GSM7373165 PBS_Plate1.A5 PBS_Plate1.A
- GSM7373166 PBS_Plate1.A6 PBS_Plate1.A
- GSM7373167 PBS_Plate1.B1 PBS_Plate1.B
- GSM7373168 PBS_Plate1.B2 PBS_Plate1.B
- GSM7373169 PBS_Plate1.B3 PBS_Plate1.B
- GSM7373170 PBS_Plate1.B4 PBS_Plate1.B
- GSM7373171 PBS_Plate1.B5 PBS_Plate1.B
- GSM7373172 PBS_Plate1.B6 PBS_Plate1.B
- GSM7373173 PBS_Plate1.C1 PBS_Plate1.C
- GSM7373174 PBS_Plate1.C2 PBS_Plate1.C
- GSM7373175 PBS_Plate1.C3 PBS_Plate1.C
- GSM7373176 PBS_Plate1.C4 PBS_Plate1.C
- GSM7373177 PBS_Plate2.A1 PBS_Plate2.A
- GSM7373178 PBS_Plate2.A2 PBS_Plate2.A
- GSM7373179 PBS_Plate2.A3 PBS_Plate2.A
- GSM7373180 PBS_Plate2.A4 PBS_Plate2.A
- GSM7373181 PBS_Plate2.A5 PBS_Plate2.A
- GSM7373182 PBS_Plate2.A6 PBS_Plate2.A
- GSM7373183 PBS_Plate2.B1 PBS_Plate2.B
- GSM7373184 PBS_Plate2.B2 PBS_Plate2.B
- GSM7373185 PBS_Plate2.B3 PBS_Plate2.B
- GSM7373186 PBS_Plate2.B4 PBS_Plate2.B
- GSM7373187 PBS_Plate2.B5 PBS_Plate2.B
- GSM7373188 PBS_Plate2.B6 PBS_Plate2.B
- GSM7373189 PBS_Plate2.C1 PBS_Plate2.C
- GSM7373190 PBS_Plate2.C2 PBS_Plate2.C
- GSM7373191 PBS_Plate2.C3 PBS_Plate2.C
- GSM7373192 PBS_Plate2.C4 PBS_Plate2.C
- GSM7373193 PBS_Plate3.A1 PBS_Plate3.A
- GSM7373194 PBS_Plate3.A2 PBS_Plate3.A
- GSM7373195 PBS_Plate3.A3 PBS_Plate3.A
- GSM7373196 PBS_Plate3.A4 PBS_Plate3.A
- GSM7373197 PBS_Plate3.A5 PBS_Plate3.A
- GSM7373198 PBS_Plate3.A6 PBS_Plate3.A
- GSM7373199 PBS_Plate3.B1 PBS_Plate3.B
- GSM7373200 PBS_Plate3.B2 PBS_Plate3.B
+ 104 more — browse all 144 samples with per-sample file links →
- GSE342046 Inflammasome Hyperactivation Disrupts Construction of the Gas Exchange Surface through the NLRP3-IL-18-TNFa Axis [RNA-seq] 17 samples shares il-1, tnf
- GSE276648 Effect of blocking the IL-10 receptor on the microglial transcriptomic signature following chronic traumatic brain injury and nasal anti-CD3 treatment 12 samples shares il-1, microglia
- GSE324526 CD36-mediated lipid-accumulation in reactive microglia drives retinal degeneration through Nlrp3-IL-1β pathway 10 samples shares il-1, microglia
- GSE222227 Induced regulatory B cells stably expressing IL-10 cure CNS autoimmunity by targeting microglia 22 samples shares il-1, microglia
- GSE239946 Signatures of IL1b, IL6 and TNFa in immune cell-types 209 samples shares tnf
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 samples shares il-1
- GSE75111 Single-cell transcriptional profiling of Th17 cells, differentiated in vitro for 48h [TGFB1_IL6-48h-IL-17A/GFP+] 151 samples shares il-1
- GSE318351 IL1A enhances TNF-induced retinal ganglion cell death 109 samples shares tnf
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.