longevity-db/ainciburu2023

Dataset Card for ainciburu_processed

Dataset Summary

This dataset comprises ~115,000 CD34+ hematopoietic stem and progenitor cells (HSPCs) profiled via 10x Genomics single-cell RNA-seq from healthy young, elderly, and myelodysplastic syndrome (MDS) patients. The data originates from:

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution
— Ainciburu et al., eLife (2023)
PMCID: PMC9904760
DOI: 10.7554/eLife.79363

Transformation Summary

The raw files were processed using the following pipeline:

1. Data Acquisition:

   • Extracted from GEO accession GSE180298, including raw matrix .h5 files and associated metadata (*_metadata.txt.gz).

2. Data Parsing and Merging:

   • Read individual 10x .h5 matrices per sample.
   • Assigned unique cell barcodes including the sample identifier.
   • Merged all into a single AnnData object with batch annotations.

3. Metadata Alignment:

   • Loaded metadata for young, elderly, and MDS samples.
   • Used barcode-sample combinations to merge metadata with cell observations.
   • Mapped cell_type, patient_id, and manually defined patient_age.

4. Final Output:

   • Saved unified dataset as processed/ainciburu_processed.h5ad.

Supported Tasks and Benchmarks

• Aging and Disease Comparison: Track HSPC shifts from youth to old age and MDS.
• Trajectory Inference: Includes pseudotime, lineage tracing via STREAM and Palantir.
• GRN Analysis: SCENIC-based regulon detection per age/disease group.
• Subtype Classification: Includes supervised label transfer from healthy to diseased donors.
• Differential Expression and GSEA: Precomputed per lineage and age/disease state.

Languages

All annotations and metadata are in English.

Dataset Structure

Data Instances

Each row is a single cell with:

• Raw gene expression (UMIs)
• Cell type annotation (e.g., HSC, MEP, GMP)
• Sample-level metadata (patient ID, condition, age)
• Batch label (sample ID)

Data Splits

No formal splits; users may stratify by:

• patient_id
• patient_age (continuous)
• condition: "young", "elderly", "mds"

Dataset Creation

Curation Rationale

Aimed to reveal regulatory, transcriptional, and population-level changes in hematopoiesis across the lifespan and in disease (MDS), using high-resolution single-cell RNA-seq and computational modeling.

Source Data

• Bone marrow CD34+ cells from 5 young (19–23y), 3 elderly (61–74y), and 4 MDS patients (54–83y).
• Sorted, sequenced using 10x Genomics Chromium.
• Raw data from GEO accession GSE180298.

Preprocessing Details

• Metadata aligned by barcode + sample combination
• Cell type labels derived from supervised classification and manual annotation
• Cell-level age assignments based on patient identity
• Final object stored as a single .h5ad file for interoperability

Licensing Information

This dataset is released under the Creative Commons BY 4.0 license. Please cite the original publication when using this dataset in your work.

Citation

@article{ainciburu2023aging,
  title={Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution},
  author={Ainciburu, Marina and Ezponda, Teresa and Berastegui, Nerea and others},
  journal={eLife},
  volume={12},
  pages={e79363},
  year={2023},
  publisher={eLife Sciences Publications Limited},
  doi={10.7554/eLife.79363}
}