Whole transcriptome analysis of purified microglia
RNA-seq (gene expression) · mouse · 18 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
- 18 samples: 5 × HX Male KO vs 5 × HX Male WT vs 4 × HX Female KO vs 4 × HX Female WTGroups 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.
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 GSE262286_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 PRJNA1090964 and SRA study SRP497316. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 18 samples.
How we read this: 4 replicated groups read from 18 sample titles; they account for 18 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.
- GSM8162586 HX Female KO rep.33 HX Female KO
- GSM8162587 HX Female KO rep.16 HX Female KO
- GSM8162588 HX Female KO rep.1 HX Female KO
- GSM8162589 HX Female KO rep.7 HX Female KO
- GSM8162590 HX Female WT rep.34 HX Female WT
- GSM8162591 HX Female WT rep.39 HX Female WT
- GSM8162592 HX Female WT rep. 31 HX Female WT
- GSM8162593 HX Female WT rep. 30 HX Female WT
- GSM8162594 HX Male KO rep. 36 HX Male KO
- GSM8162595 HX Male KO rep. 6 HX Male KO
- GSM8162596 HX Male KO rep. 9 HX Male KO
- GSM8162597 HX Male KO rep. 17 HX Male KO
- GSM8162598 HX Male KO rep. 40 HX Male KO
- GSM8162599 HX Male WT rep. 13 HX Male WT
- GSM8162600 HX Male WT rep. 37 HX Male WT
- GSM8162601 HX Male WT rep. 10 HX Male WT
- GSM8162602 HX Male WT rep. 11 HX Male WT
- GSM8162603 HX Male WT rep. 14 HX Male WT
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares microglia
- GSE293041 Single-cell transcriptome analysis of wildtype, TREM2 knockout, GPR34 knock-out or TREM2/GPR34 double knock-out primary microglia from wildtype and APP knock-in mice (8 months) 10 samples shares microglia
- GSE274057 Whole transcriptome sequencing for upper tract urothelial carcinoma (UTUC) of BALB/c female mice treated with N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN) 37 samples shares whole
- GSE272755 Transcriptional effects of lysosome stress on mouse bone marrow-derived macrophages and primary microglia 263 samples shares microglia
- GSE292919 Whole transcriptomes analyses of organoids derived from Mist1Cre/ERT2 mice corpus with oxidative stress 27 samples shares whole
- GSE254229 ALS/FTD-linked TBK1 deficiency in microglia induces an aged-like microglial signature and drives social recognition deficits in mice 141 samples shares microglia
- GSE309348 Whole transcriptome sequencing of UPEC-infected testis and epididymis (5d) following depletion of CX3CR1+ macrophages 18 samples shares whole
- GSE98969 Single cell RNA-seq identifies a unique microglia type associated with Alzheimer’s disease [RNA] 97 samples shares microglia
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.