Locus Coeruleus noradrenergic axon loss drives olfactory dysfunction in Alzheimer's disease
RNA-seq (gene expression) · mouse · 16 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
- 16 samples: 4 × WT_m vs 4 × KI_f vs 4 × WT_f vs 4 × KI_mGroups 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 GSE302245_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 PRJNA1284072 and SRA study SRP596060. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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.
- GSM9100425 WT_m_REP1 WT_m
- GSM9100426 WT_m_REP2 WT_m
- GSM9100427 KI_f_REP1 KI_f
- GSM9100428 WT_f_REP1 WT_f
- GSM9100429 KI_f_REP2 KI_f
- GSM9100430 KI_m_REP1 KI_m
- GSM9100431 KI_m_REP2 KI_m
- GSM9100432 WT_f_REP2 WT_f
- GSM9100433 WT_m_REP3 WT_m
- GSM9100434 WT_m_REP4 WT_m
- GSM9100435 KI_f_REP3 KI_f
- GSM9100436 WT_f_REP3 WT_f
- GSM9100437 KI_f_REP4 KI_f
- GSM9100438 WT_f_REP4 WT_f
- GSM9100439 KI_m_REP3 KI_m
- GSM9100440 KI_m_REP4 KI_m
- GSE252120 Oxidative stress induced telomere instability/damage drives T cell dysfunction in cancer 32 samples shares dysfunction, drives
- GSE334551 NAD+ Deficiency Drives Metabolic Dysfunction-Associated Atrial Fibrillation 29 samples shares dysfunction, drives
- GSE291086 Neuronal ABCA7 deficiency aggravates mitochondrial dysfunction and neurodegeneration in Alzheimer’s disease 24 samples shares dysfunction, alzheimer
- GSE291921 Linking trajectories of cerebrovascular remodeling and dysfunction to cross-species brain vessel transcriptome in Alzheimer’s disease 24 samples shares dysfunction, alzheimer
- GSE232098 Innate immune memory after brain injury drives inflammatory cardiac dysfunction 20 samples shares dysfunction, drives
- GSE310612 Astrocytic FABP5 drives cerebellar white matter dysfunction in multiple system atrophy by promoting TNF signaling and ferroptosis 15 samples shares dysfunction, drives
- GSE302342 Lack of cortistatin drives neuroimmune and vascular dysfunction in brain ischemia 14 samples shares dysfunction, drives
- GSE298755 GATA2 deficiency drives a profibrotic program and metabolic dysfunction in alveolar macrophages 14 samples shares dysfunction, drives
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.