Cui S et al. (2025) Nucleic Acids Research [In Preparation]. See cite section below.
Quick Start Guide
๐งฌ
Researchers
Browse the dataset catalog โ Filter by species/tissue/age โ Download processed h5ad matrices โ Explore UMAP in the Atlas viewer โ Use the API for programmatic access.
๐ฉบ
Clinicians
Navigate to Longevity Maps โ Select tissue of interest โ Review age-associated cell type changes โ Cross-reference with clinical aging markers in the Assessment module.
๐ป
Bioinformaticians
Access REST API โ Query genes across species and tissues โ Download standardized matrices โ Use the cross-species comparison tool โ Cite source datasets via the Reference table.
Six-Step Workflow
1
Browse: Navigate to Browse Datasets to view the full catalog of 1,407 curated datasets with metadata.
2
Filter: Use the filter bar to narrow by species, tissue, age group, and sequencing modality.
3
Explore: Click any dataset to open it in the Interactive Atlas โ view UMAP, cluster annotations, and marker genes.
4
Query: Use the Gene Expression tool to visualize expression of any gene across cell types, tissues, and ages.
5
Download: Access processed matrices (AnnData/h5ad) or CSV metadata from the Download page. Raw data links to GEO/NGDC.
6
Cite: Use the citation block below (#cite) to cite LACA and individual source datasets in your publications.
Note: LACA currently provides curated metadata and processed expression matrices. Integrated single-file downloads (merged h5ad) are planned for v2.0. Raw sequencing data must be accessed through the original repositories listed in each dataset record.
Selection Methodology
Inclusion Criteria
Single-cell or single-nucleus RNA-seq data from one or more of the five focal species
Samples must span at least two distinct age groups (development, young, middle-aged, old, geriatric)
Dataset published in a peer-reviewed journal or deposited in GEO/NGDC with a data availability statement
Minimum 5,000 cells after quality control; published cell type annotations or annotatable with standard markers
Tissue type covered by the LACA anatomical ontology (20+ tissues across organ systems)
Quality & Feasibility
Doublet rate < 10% or explicit doublet removal documented in the source publication
Ambient RNA contamination addressed (SoupX, CellBender, or equivalent)
Cell type annotations verified against canonical marker gene panels
Metadata completeness: age, sex, tissue, and sequencing platform all recorded
Data available in a standardized format (h5ad, loom, Seurat RDS, or 10x MEX) enabling re-analysis
Data Availability Statement
All datasets integrated into LACA are derived from publicly available repositories. Processed expression matrices
and cell metadata are hosted at http://lcatlas.nmu.edu.cn/ and are
freely downloadable without registration. Raw sequencing data remain at the original submission repositories listed in each dataset record.
Code & Software Availability: Web portal source code is available at
github.com/LongevityCellAtlas.
Data processing pipelines (Scanpy, Seurat, CellTypist) are documented in the Methods section of the companion manuscript.
A Snakemake-based reproducible pipeline is planned for public release in v2.0.
Ethics & Data Privacy
IRB & Data Provenance
All human datasets integrated into LACA were originally collected under institutional review board (IRB) approval at their originating institutions. LACA does not collect new patient data; it aggregates and re-analyses publicly deposited datasets. Each dataset record links to the original publication and data availability statement, where IRB information is provided.
De-identification Checklist
No individual-level identifiers (name, DOB, address) included
Age recorded as binned categories (not exact dates of birth)
Sample-level metadata limited to: age group, sex, tissue, health status
Human datasets flagged for controlled access where applicable
Controlled-access datasets linked to dbGaP/EGA; not mirrored
How to Cite
Citing the LACA Database
Cui S*, Yu Y*, Xu S*, Chen D*, Yin S, Chen T, Li C, Wen Y, Tian S, Guan Y, Yang X, Wang S, et al.
(2025) Longevity & Aging Cell Atlas: A Cross-Species Single-Cell Transcriptomic Database for Aging Research.
Nucleic Acids Research, [In Preparation].
BibTeX
@article{LACA2025,
title = {Longevity & Aging Cell Atlas: A Cross-Species Single-Cell Transcriptomic Database for Aging Research},
author = {Cui, Shufang and Yu, Yizhi and Xu, Sheng and Chen, Dongsheng and Yin, Shulei and Chen, Taoyu and others},
journal = {Nucleic Acids Research},
year = {2025},
note = {In Preparation},
url = {http://lcatlas.nmu.edu.cn/}
}
When using individual datasets from LACA, please also cite the original source publication listed in each dataset record. Dataset-specific citations are provided on each dataset detail page.
Version History & Update Policy
Release Timeline
v1.0
2025-06
Initial Release [Current]
Core catalog of 48 datasets ยท 5 species ยท Interactive atlas ยท Gene expression query ยท CSV export
Pilot dataset: NMR multi-tissue ยท Dataset metadata schema established
Update Policy
Review Frequency
Dataset inventory reviewed quarterly. Each cycle verifies cell counts, metadata completeness, and checks for retracted or superseded publications.
Version Numbering
Semantic versioning: minor increments (1.0 โ 1.1) for dataset additions; major increments (1.x โ 2.0) for schema changes or platform overhauls.
Deprecation
Retracted datasets are marked [Deprecated] and removed from default views; full record retained in version history for reproducibility.
Long-term Commitment
LACA is maintained by Naval Medical University and Suzhou Institute of Systems Medicine. Infrastructure funding secured through 2028; committed to minimum 5-year URL stability.