Effect of Bacteroides fragilis administration on microglia in WT and the APP-PS1 model of Alzheimer's disease [Bfrag]
RNA-seq (gene expression) · mouse · 15 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
- 15 samples: 13 distinct titles, 1 of them repeatedGroups 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.
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 GSE215438_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 PRJNA876228 and SRA study SRP395374. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 15 sample titles: 13 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.
- GSM6637146 SM-J6UU7
- GSM6637147 SM-J6UU8
- GSM6637148 SM-J6UU9
- GSM6637149 SM-J6UUA
- GSM6637150 SM-J6UUE
- GSM6637151 SM-J6UUF
- GSM6637152 SM-J6UUG
- GSM6637153 SM-J6UUH
- GSM6637154 SM-J6UUB
- GSM6637155 SM-J6UUC
- GSM6637156 SM-J6UUD
- GSM6637157 SM-J6UUI
- GSM6637158 SM-J6UUJ
- GSM6637159 SM-J6UUK
- GSM6637160 SM-J6UUL
- GSE98969 Single cell RNA-seq identifies a unique microglia type associated with Alzheimer’s disease [RNA] 97 samples shares microglia, alzheimer
- GSE223424 Immune checkpoint TIM-3 regulates microglia and Alzheimer’s disease 57 samples shares microglia, alzheimer
- GSE273690 Adhesion G protein-coupled receptor ADGRG1 promotes protective microglial response in Alzheimer’s disease 48 samples shares microglia, alzheimer
- GSE277167 Protective variant in PLCγ2 mitigates Alzheimer’s disease associated pathology via enhancing beneficial microglia functions 31 samples shares microglia, alzheimer
- GSE254104 Alzheimer’s disease-linked risk alleles elevate microglial cGAS-associated senescence and neurodegeneration in a tauopathy model [snRNAseq] 27 samples shares microglia, alzheimer
- GSE254103 Alzheimer’s disease-linked risk alleles elevate microglial cGAS-associated senescence and neurodegeneration in a tauopathy model [bulk_RNAseq] 24 samples shares microglia, alzheimer
- GSE327604 Epigenetic control of microglial mitochondrial immunity by KAT7 drives Alzheimer’s disease pathogenesis [RNA-Seq] 12 samples shares microglia, alzheimer
- GSE296768 Plaque-induced transcriptional reprogramming of microglia towards lymphoid receptor expression protects against Alzheimer's disease [scRNA-seq] 12 samples shares microglia, alzheimer
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.