Arresting the Bad Seed: HDAC3 Regulates Proliferation of Different Microglia after Ischemic Stroke [RNA-seq]
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
- Arresting the bad seed: HDAC3 regulates proliferation of different microglia after ischemic strokeScience advances · 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 GSE220042_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 PRJNA908103 and SRA study SRP411181. 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.
- GSM6783848 WT_Sham_rep1 [RNA-seq]
- GSM6783849 WT_Sham_rep2 [RNA-seq]
- GSM6783850 WT_Sham_rep3 [RNA-seq]
- GSM6783851 HDAC3miKO_Sham_rep1 [RNA-seq]
- GSM6783852 HDAC3miKO_Sham_rep2 [RNA-seq]
- GSM6783853 HDAC3miKO_Sham_rep3 [RNA-seq]
- GSM6783854 WT_tFCI_rep1 [RNA-seq]
- GSM6783855 WT_tFCI_rep2 [RNA-seq]
- GSM6783856 WT_tFCI_rep3 [RNA-seq]
- GSM6783857 HDAC3miKO_tFCI_rep1 [RNA-seq]
- GSM6783858 HDAC3miKO_tFCI_rep2 [RNA-seq]
- GSM6783859 HDAC3miKO_tFCI_rep3 [RNA-seq]
- GSE220043 Arresting the Bad Seed: HDAC3 Regulates Proliferation of Different Microglia after Ischemic Stroke 22 samples shares hdac3, proliferation, arresting, different, microglia, ischemic, stroke
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- GSE283700 RNA-sequencing of SVF-derived preadipocytes from inguinal adipose tissue of male mice differentiating under control conditions or treated with CGRP 15 samples shares different, rna-seq
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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.