Single-cell profiling reveals RAB13+ endothelial cells and profibrotic mesenchymal cells in aged human bone marrow
Single-cell RNA-seq · human · 12 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 7 × Elderly vs 5 × YoungGroups 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
- Single-Cell Profiling Reveals RAB13(+) Endothelial Cells and Profibrotic Mesenchymal Cells in Aged Human Bone MarrowAging cell · 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 GSE305558_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 PRJNA1306503 and SRA study SRP609112. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 2 replicated groups read from 12 sample titles; they account for 12 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.
- GSM9179364 Young1 Young
- GSM9179365 Young2 Young
- GSM9179366 Young3 Young
- GSM9179367 Young4 Young
- GSM9179368 Young5 Young
- GSM9179369 Elderly1 Elderly
- GSM9179370 Elderly2 Elderly
- GSM9179371 Elderly3 Elderly
- GSM9179372 Elderly4 Elderly
- GSM9179373 Elderly5 Elderly
- GSM9179374 Elderly6 Elderly
- GSM9179375 Elderly7 Elderly
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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.