Early amyloid-induced changes in microglia gene expression in APP/PS1 mice [bulk RNA-seq]
Single-cell RNA-seq · mouse · 24 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 24 samples: 6 conditions, mostly with about 4 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
- Early amyloid-induced changes in microglia gene expression in male APP/PS1 miceJournal of neuroscience research · 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 GSE226937_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA942288 and SRA study SRP426297. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 23 samples.
How we read this: 6 replicated groups read from 24 sample titles; they account for 23 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.
- GSM7088612 App_hip_mic_4m_wt_1 App_hip_mic_4m_wt
- GSM7088613 App_hip_mic_4m_wt_2 App_hip_mic_4m_wt
- GSM7088614 App_hip_mic_4m_wt_3 App_hip_mic_4m_wt
- GSM7088615 App_hip_mic_4m_wt_4 App_hip_mic_4m_wt
- GSM7088616 App_hip_mic_4m_tg_1 App_hip_mic_4m_tg
- GSM7088617 App_hip_mic_4m_tg_2 App_hip_mic_4m_tg
- GSM7088618 App_hip_mic_4m_tg_3 App_hip_mic_4m_tg
- GSM7088619 App_hip_mic_4m_tg_4 App_hip_mic_4m_tg
- GSM7088620 App_hip_mic_6m_wt_1 App_hip_mic_6m_wt
- GSM7088621 App_hip_mic_6m_wt_2 App_hip_mic_6m_wt
- GSM7088622 App_hip_mic_6m_wt_3 App_hip_mic_6m_wt
- GSM7088623 App_hip_mic_6m_wt_4 App_hip_mic_6m_wt
- GSM7088624 App_hip_mic_6m_tg_1 App_hip_mic_6m_tg
- GSM7088625 App_hip_mic_6m_tg_2 App_hip_mic_6m_tg
- GSM7088626 App_hip_mic_6m_tg_3 App_hip_mic_6m_tg
- GSM7088627 App_hip_mic_6m_tg_4 App_hip_mic_6m_tg
- GSM7088628 App_hip_mic_9m_wt_1 App_hip_mic_9m_wt
- GSM7088629 App_hip_mic_9m_wt_2_4
- GSM7088630 App_hip_mic_9m_wt_3 App_hip_mic_9m_wt
- GSM7088631 App_hip_mic_9m_wt_5 App_hip_mic_9m_wt
- GSM7088632 App_hip_mic_9m_tg_1 App_hip_mic_9m_tg
- GSM7088633 App_hip_mic_9m_tg_2 App_hip_mic_9m_tg
- GSM7088634 App_hip_mic_9m_tg_3 App_hip_mic_9m_tg
- GSM7088635 App_hip_mic_9m_tg_4 App_hip_mic_9m_tg
- GSE226938 Early amyloid-induced changes in microglia gene expression in APP/PS1 mice [scRNA-seq] 36 samples shares app, ps1, amyloid-induced, microglia, changes, rna-seq, early
- GSE275510 Deciphering Motor Dysfunction and Microglial Activation in mThy1-α-Synuclein Mice: A Comprehensive Study of Behavioral, Gene Experssion, and Methylation Changes [RNA-Seq] 20 samples shares microglia, changes, rna-seq
- GSE290194 Repair-Associated Macrophages Increase after Early-phase Microglia Attenuation to Promote Ischemic Stroke Recovery [scRNA-Seq] 16 samples shares microglia, rna-seq, early
- GSE222996 The immune landscape of the “deregulated host response” in sepsis: newly emerging MDSCs with high expression of CD47 leads to B cell suppression via App-CD74 signaling [RNA-seq] 61 samples shares app, rna-seq
- GSE225237 Reevaluation by CRISPR-Cas9 approach reveals multiple lincRNAs dispensable for pluripotency maintenance and SNORA73 essential for pluripotency exit (RNA-Seq) 12 samples shares app, rna-seq
- GSE282851 Functional mapping of epigenomic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes [scRNA-seq] 10 samples shares app, rna-seq
- GSE217970 Mapping putative enhancers in mouse oocyte and early embryo reveals TCF3/12 as key folliculogenesis regulators 164 samples shares app, early
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares microglia, rna-seq
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.