PhyloGNN
Practical graph learning tools for phylogenetic trees.
PhyloGNN converts ete3.Tree objects into PyTorch Geometric Data graphs,
adds deterministic node features, and supports local GNN training workflows
on those graph samples.
Fastest path
Install
Start with the core package and add optional extras only for docs, BEAST
file input, or experiment tracking.
Quickstart
Build a small ete3.Tree, attach features, convert it to graph data,
run a tiny training smoke test, and print a prediction.
User Guide
Follow the full workflow from tree input through feature engineering, graph conversion, datasets, training, configuration, and tracking.
Examples
Launch six runnable scripts that cover feature engineering, graph conversion, tree I/O, training, TOML configuration, and prediction.
Reference
Look up curated public APIs for data conversion, models, training, I/O, and utilities.
Typical workflow: tree input → feature engineering → graph conversion → training → metrics tracking when needed → API lookup for implementation details.
User Documentation