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To test this, we applied both a strict tree reconciliation method and our previously described species-overlap algorithm to predict orthology relationships of all yeast genes.
Nonetheless, relaxing the strict tree requirement can reposition groups and highlight cases where strong disagreement exists.
We say that a set S ≠ 𝒳 is an ST-set (strict tree set) w.r.t.
Even if very strict tree selection criteria are applied, there are still likely to be biases in the data set.
In particular, some researchers proposed reconstructing phylogenetic networks, rhizomes or syntheses of life instead of a strict tree, making it possible to distinguish the vertical backbone (tracking the lineage of dividing cells) from horizontal transfers, which were represented by additional lateral branches.
The current retention by many evolutionary biologists of a strict tree metaphor for prokaryotes, despite its inability to account for the observations, presents a serious barrier to our understanding of prokaryotic evolution and is hard to square with most accounts of how science should be done.
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Next, a strict tree-reconciliation algorithm was used [17].
A conservative approach using the "strict" tree-based method should be used initially in large-scale identification systems.
Based on our results, we suggest a conservative approach that initially uses a "strict" tree-based criterion in large-scale assignment systems.
A liberal tree-based criterion assigned 83% of queries accurately to genus, 74% to tribe and 90% to subfamily, compared to a strict tree-based criterion, which assigned 75% of queries accurately to genus, 66% to tribe and 84% to subfamily, with a library containing 100% of available species (but excluding the species of the query).
The strict consensus tree (tree not shown) was similar but less resolved compared to the Bayesian consensus tree.
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