Data from: The influence of the number of tree searches on maximum likelihood inference in phylogenomics

Maximum likelihood (ML) phylogenetic inference is widely used in
phylogenomics. As heuristic searches most likely find suboptimal trees, it
is recommended to conduct multiple (e.g., ten) tree searches in
phylogenetic analyses. However, beyond its positive role, how and to what
extent multiple tree searches aid ML phylogenetic inference remains poorly
explored. Here, we found that a random starting tree was not as effective
as the BioNJ and parsimony starting trees in inferring ML gene tree and
that RAxML-NG and PhyML were less sensitive to different starting trees
than IQ-TREE. We then examined the effect of the number of tree searches
on ML tree inference with IQ-TREE and RAxML-NG, by running 100 tree
searches on 19,414 gene alignments from 15 animal, plant, and fungal
phylogenomic datasets. We found that the number of tree searches
substantially impacted the recovery of the best-of-100 ML gene tree
topology among 100 searches for a given ML program. In addition, all of
the concatenation-based trees were topologically identical if the number
of tree searches was ≥ 10. Quartet-based ASTRAL trees inferred from 1 to
80 tree searches differed topologically from those inferred from 100 tree
searches for 6 /15 phylogenomic datasets. Lastly, our simulations showed
that gene alignments with lower difficulty scores had a higher chance of
finding the best-of-100 gene tree topology and were more likely to yield
the correct trees.