Spatial transcriptomic profiling of the human aortic valve reveals cellular sex differences near sites of calcification
Single-cell RNA-seq · human · 17 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 17 samples: 17 samples, each with a distinct title — no replicated groupsGroups 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.
- Paper
- Spatial and Single-Cell Mapping Reveals Valvular Interstitial Cell and Macrophage Sex Differences in Calcific Aortic Valve DiseaseArteriosclerosis, thrombosis, and vascular biology · 2026
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 GSE306288_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1310428 and SRA study SRP612249. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 17 sample titles: 17 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.
- GSM9196841 patient 1 human aortic valve leaflet cells, male, diseased
- GSM9196842 patient 2 human aortic valve leaflet cells, male, healthy
- GSM9196843 patient 5 human aortic valve leaflet cells, male, diseased
- GSM9196844 patient 10 human aortic valve leaflet cells, male, healthy
- GSM9196845 patient 22 human aortic valve leaflet cells, male, healthy
- GSM9196846 patient 1A human aortic valve leaflet tissue, male, diseased
- GSM9196847 patient 1B human aortic valve leaflet tissue, male, diseased
- GSM9196848 patient 6A human aortic valve leaflet tissue, female, diseased
- GSM9196849 patient 6B human aortic valve leaflet tissue, female, diseased
- GSM9759905 patient 15 human aortic valve leaflet cells, male, diseased
- GSM9759906 patient 21 human aortic valve leaflet cells, female, diseased
- GSM9759907 patient 23 human aortic valve leaflet cells, female, diseased
- GSM9759908 patient 27 human aortic valve leaflet cells, female, diseased
- GSM9759909 patient 18V human aortic valve leaflet tissue, female, diseased
- GSM9759910 patient 20V human aortic valve leaflet tissue, male, diseased
- GSM9759911 patient 23V human aortic valve leaflet tissue, female, diseased
- GSM9759912 patient 29V human aortic valve leaflet tissue, male, diseased
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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.