PFOS exposure on the brain transcriptome of aged mice
RNA-seq (gene expression) · mouse · 9 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
- 9 samples: 3 × C vs 3 × L vs 3 × HGroups 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 GSE319302_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 PRJNA1422796 and SRA study SRP676591. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9515059 C1 C
- GSM9515060 C2 C
- GSM9515061 C3 C
- GSM9515062 L1 L
- GSM9515063 L2 L
- GSM9515064 L3 L
- GSM9515065 H1 H
- GSM9515066 H2 H
- GSM9515067 H3 H
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- GSE270016 Rejuvenation of aged oocyte through exposure to young follicular microenvironment 45 samples shares exposure, aged
- GSE290810 ALS/FTD-linked TBK1 deficiency in microglia induces an aged-like microglial signature and drives social recognition deficits [FACS_SpinalCord_Microglia & LPS_Brain_SpinalCord] 35 samples shares brain, aged
- GSE341988 Sequential pathogen exposure normalizes the brain neuroimmune microenvironment and reveals a tissue-resident memory CD8 T cell-microglia axis shaping adult neurogenesis 8 samples shares exposure, brain
- GSE332794 Epigenomic profiling of H3K27ac in mouse brain regions under morphine and LPS exposure 206 samples shares exposure, brain
- GSE98816 Single cell RNA-seq of mouse brain vascular transcriptomes 3186 samples shares brain
- GSE254229 ALS/FTD-linked TBK1 deficiency in microglia induces an aged-like microglial signature and drives social recognition deficits in mice 141 samples shares aged
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares brain
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.