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Multi-omics and 3D-imaging reveal bone heterogeneity and unique calvaria cells in neuroinflammation

GSE192616 Mus musculus (mouse) RNA-seq (gene expression) 295 samples Submitted 2023/07/15 Platform GPL21103Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 295 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
295 samples
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.
Summary (written by the submitters)
The bone marrow in the skull is important for shaping immune responses in the brain and meninges, but its molecular makeup in comparison to other bones in mice and humans remains unclear. Here, we show that the skull has the most distinct transcriptomic profile compared to other bones in states of health and injury, characterized by a late-stage neutrophil phenotype.
Read the full summary ↓
In humans, proteome analysis reveal that the skull marrow is the most distinct, with differentially expressed neutrophil-related pathways and a unique synaptic protein signature. 3D imaging demonstrates the structural and cellular details of human skull-meninges connections compared to veins. Lastly, using TSPO-PET imaging, we show that the skull bone marrow reflects inflammatory brain responses with a disease-specific spatial distribution in patients with various neurological disorders. The unique molecular profile, anatomical, and functional connections of the skull show its potential as a new site for diagnosing, monitoring, and treating brain diseases.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE192616_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA792403 and SRA study SRP352496. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 295 more — browse all 295 samples with per-sample file links →

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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.