PT  - JOURNAL ARTICLE
AU  - Julia Haag
AU  - Dimitri Höhler
AU  - Ben Bettisworth
AU  - Alexandros Stamatakis
TI  - From Easy to Hopeless - Predicting the Difficulty of Phylogenetic Analyses
AID  - 10.1101/2022.06.20.496790
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.06.20.496790
4099  - http://biorxiv.org/content/early/2022/06/21/2022.06.20.496790.short
4100  - http://biorxiv.org/content/early/2022/06/21/2022.06.20.496790.full
AB  - Phylogenetic analyses under the Maximum Likelihood model are time and resource intensive. To adequately capture the vastness of tree space, one needs to infer multiple independent trees. On some datasets, multiple tree inferences converge to similar tree topologies, on others to multiple, topologically highly distinct yet statistically indistinguishable topologies. At present, no method exists to quantify and predict this behavior. We introduce a method to quantify the degree of difficulty for analyzing a dataset and present Pythia, a Random Forest Regressor that accurately predicts this difficulty. Pythia predicts the degree of difficulty of analyzing a dataset prior to initiating Maximum Likelihood based tree inferences. Pythia can be used to increase user awareness with respect to the amount of signal and uncertainty to be expected in phylogenetic analyses, and hence inform an appropriate (post-)analysis setup. Further, it can be used to select appropriate search algorithms for easy-, intermediate-, and hard-to-analyze datasets.Competing Interest StatementThe authors have declared no competing interest.