Resolving competing evolutionary histories in joint ancestral state reconstruction

This repository contains simulation data, empirical data, and analysis code for a study evaluating joint uncertainty in discrete character ancestral state reconstruction (ASR). We compare joint and marginal reconstruction approaches across a range of simulated conditions and apply these methods to an empirical dataset of carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates from a Long-Term Acute Care Hospital (LTACH).
, , # DATA FOR: Resolving competing evolutionary histories in joint ancestral state reconstruction

All files below are in joint-unc.zip which includes all of the code for simulating and comparing our new joint uncertainty methods.

## General Information

**Corresponding author information**

```
Name: James Boyko
ORCID: 0000-0003-0952-169X
Affiliation: University of Michigan
```

**Related publication**

```
[PLACEHOLDER: Full citation once published]
```

## Notes on file naming conventions

Simulation condition files follow the pattern:

`[method]_n[ntaxa]_k[nstates]_q[rate]_[model]`

where:

- `[method]` is the reconstruction approach used to compute confidence intervals:
- `simmap` — stochastic mapping
- `pupko` — Pupko joint reconstruction
- `marginal` — marginal reconstruction
- `[ntaxa]` is the number of taxa in the simulated tree (always `101` in this study)
- `[nstates]` (`k`) is the number of discrete character states (`2` or `3`)
- `[rate]` (`q`) is the per-branch transi..., ,