MAPT-derived circTau6 induces tau pathogenesis and neurodegeneration by encoding Tau variants
RNA-seq (gene expression) · mouse · 10 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
- 10 samples: 5 × con vs 5 × T6Groups 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 GSE329170_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 PRJNA1458083 and SRA study SRP695178. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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.
- GSM9698559 con-1 con
- GSM9698560 con-2 con
- GSM9698561 con-3 con
- GSM9698562 con-4 con
- GSM9698563 con-5 con
- GSM9698564 T6-1 T6
- GSM9698565 T6-2 T6
- GSM9698566 T6-3 T6
- GSM9698567 T6-4 T6
- GSM9698568 T6-5 T6
- GSE255633 Region-specific pathogenesis and dissipation of intraregional heterogeneity in cerebellar neurodegeneration 49 samples shares neurodegeneration, pathogenesis
- GSE103334 Temporal tracking of microglia activation in neurodegeneration at single-cell resolution 2208 samples shares neurodegeneration
- GSE254996 ACSS2 upregulation enhances neuronal resilience to aging and neurodegeneration [RNA-seq] 98 samples shares neurodegeneration
- GSE304212 Molecular Pathogenesis of Alzheimer's Disease Onset in a Mouse Model: Effects of Cannabidiol Treatment 60 samples shares pathogenesis
- GSE300423 LINE-1 retrotransposition in a mouse TDP-43 model of neurodegeneration marks motor cortex neurons for cell-intrinsic and cell non-autonomous programmed cell death. 45 samples shares neurodegeneration
- GSE297457 A role for the cholinergic neuron circadian clock in RNA metabolism and mediating neurodegeneration 44 samples shares neurodegeneration
- GSE278050 KLF13 promotes SLE Pathogenesis by modifying chromatin accessibility of key proinflammatory cytokine genes [RNA-seq] 42 samples shares pathogenesis
- GSE264189 Premature aging effects on COVID-19 pathogenesis: new insights from mouse models 42 samples shares pathogenesis
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.