General layout: landscape A1, divided into six boxes; title in top-middle
Target audience: people who might want to do things with tree sequences in python
Proposed collaboration structure: each box is a jupyter notebook that I put in latex at the last moment
- tskit logo
- very brief intro/description statement
- what's on the website
- emphasize that (a) it does stuff fast and quick, and (b) it gives us a time dimension
- tagline: "launching your genomes into the time dimension"?
- how to contribute
- bigger ecosystem: what else uses tskit?
pretty and useful things
top-level metadata for all your recording needs
e.g., "find the trees with at least five nodes above time 100" or "compute the average number of siblings of "
- C, Rust, Python interfaces (also R via reticulate?)
- In-browser e.g. via pyodide/Jupyterlite - ideal for workshops/teaching!
- SLiM fwdpy11, msprime, tsinfer, ?relate
- Is an ARG library
- VCF output
pi-along-the-genome, IBD blocks; cross-coalescent rates?
- Efficient array access (e.g. for numba)
- Tree metrics (balance/imbalance)
- Reference sequence and alignments
- Structural ops (e.g. decapitate)
- Parallelization?