A Python-based compendium of GPU-optimized aging clocks.
Project description
🐍 pyaging: a Python-based compendium of GPU-optimized aging clocks
pyaging
is a cutting-edge Python package designed for the longevity research community, offering a comprehensive suite of GPU-optimized biological aging clocks.
Installation - Search, cite, and get metadata - Bulk DNA methylation - Bulk histone mark ChIP-Seq - Bulk ATAC-Seq - Bulk RNA-Seq - Blood chemistry - API Reference
With a growing number of aging clocks, comparing and analyzing them can be challenging. pyaging
simplifies this process, allowing researchers to input various molecular layers (DNA methylation, histone ChIP-Seq, ATAC-seq, transcriptomics, etc.) and quickly analyze them using multiple aging clocks, thanks to its GPU-backed infrastructure. This makes it an ideal tool for large datasets and multi-layered analysis.
📝 To-Do List
- Integrate scAge and scRNAseq clocks (and datasets)
- Incorporate murine DNA methylation and proteomic clocks (and datasets)
❓ Can't find an aging clock?
If you have recently developed an aging clock and would like it to be integrated into pyaging
, please email us. We aim to incorporate it within two weeks! We are also happy to adapt to any licensing terms for commercial entities.
💬 Community Discussion
For coding-related queries, feedback, and discussions, please visit our GitHub Issues page.
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