Online appendix and simulated data sets for assesment of Birth-Death Exposed-Infectious (BDEI) phylodynamic model estimators

The birth-death exposed-infectious (BDEI) phylodynamic model describes the transmission of pathogens featuring an incubation period (when there is a delay between the moment of infection and becoming infectious, as for Ebola and SARS-CoV-2), and permits its estimation along with other parameters, from time-scaled phylogenetic trees.
We implemented a highly parallelizable estimator for the BDEI model in a maximum likelihood framework (PyBDEI) using a combination of numerical analysis methods for efficient equation resolution. This dataset contains the assessment of PyBDEI in comparison with a Bayesian implementation in BEAST2 (mtbd package) and a deep learning estimator PhyloDeep: the parameter values estimated by the 3 tools.The PyBDEI and the theoretical findings behind it are described in A Zhukova, F Hecht, Y Maday, and O Gascuel. Fast and Accurate Maximum-Likelihood Estimation of Multi-Type Birth-Death Epidemiological Models from Phylogenetic Trees Syst Biol 2023. This dataset conta..., Simulated data
We assessed the performance of our estimator on two data sets from Voznica et al. 2021 (accessible at (doi.org/10.5281/zenodo.7358555)):

medium, a data set of 100 medium-sized trees (200 − 500 tips),

large, a data set of 100 large trees (5 000 − 10 000 tips)

The data were downloaded from github.com/evolbioinfo/phylodeep (also accessible at (doi.org/10.5281/zenodo.7358555), under GNU GPL v3 licence).
To produce medium trees, Voznica et al. generated 10 000 trees with 200 − 500 tips under the BDEI model, with the parameter values sampled uniformly at random within the following boundaries:

incubation period 1/µ ∈ [0.2, 50]
basic reproductive number R_0 = λ/ψ ∈ [1, 5]
infectious period 1/ψ ∈ [1, 10].

Then randomly selected 100 out of those 10 000 trees to evaluate them with the gold standard method, BEAST2.
For 100 large tree generation, the same parameter values as for the 100 medium ones were used, but the tree size varied between 5000 and 10 000 tips.
Large forest d..., The data are uploaded as zip archives. The simulated data files within the archives can be opened with a text editor. The Appendix.pdf file can be opened with Adobe Acrobat or any other PDF viewer., # Online Appendix and simulated data for Zhukova *et al.* *Syst Biol* 2023

## Online Appendix

Contains Fig S1-S3 and Table S1.

## Simulated data

We assessed the performance of our estimator on two data sets from [Voznica ](https://doi.org/10.1101/2021.03.11.435006)*[et al.](https://doi.org/10.1101/2021.03.11.435006)*[ 2021](https://doi.org/10.1101/2021.03.11.435006) (accessible at [(doi.org/10.5281/zenodo.7358555)](https://doi.org/10.5281/zenodo.7358555)):

1. **medium**, a data set of 100 medium-sized trees (200 − 500 tips),
2. **large**, a data set of 100 large trees (5 000 − 10 000 tips)

The data were downloaded from [github.com/evolbioinfo/phylodeep](https://github.com/evolbioinfo/phylodeep) (also accessible at [(doi.org/10.5281/zenodo.7358555)](https://doi.org/10.5281/zenodo.7358555), under GNU GPL v3 licence).
To produce medium trees, Voznica et al. generated 10 000 trees with 200 − 500 tips under the BDEI model, with the parameter values sampled uniformly at random within th...