Phylogenetic trees are used to analyze and visualize evolution. However, trees can be imperfect datatypes when summarizing multiple trees. This is especially problematic when accommodating for biological phenomena such as horizontal gene transfer, incomplete lineage sorting, and hybridization, as well as topological conflict between datasets. Additionally, researchers may want to combine information from sets of trees that have partially overlapping taxon sets. To address the problem of analyzing sets of trees with conflicting relationships and partially overlapping taxon sets, we introduce methods for aligning, synthesizing and analyzing rooted phylogenetic trees within a graph, called a tree alignment graph (TAG). The TAG can be queried and analyzed to explore uncertainty and conflict. It can also be synthesized to construct trees, presenting an alternative to supertrees approaches. We demonstrate these methods with two empirical datasets. In order to explore uncertainty, we constructed a TAG of the bootstrap trees from the Angiosperm Tree of Life project. Analysis of the resulting graph demonstrates that areas of the dataset that are unresolved in majority-rule consensus tree analyses can be understood in more detail within the context of a graph structure, using measures incorporating node degree and adjacency support. As an exercise in synthesis (i.e., summarization of a TAG constructed from the alignment trees), we also construct a TAG consisting of the taxonomy and source trees from a recent comprehensive bird study. We synthesized this graph into a tree that can be reconstructed in a repeatable fashion and where the underlying source information can be updated. The methods presented here are tractable for large scale analyses and serve as a basis for an alternative to consensus tree and supertree methods. Furthermore, the exploration of these graphs can expose structures and patterns within the dataset that are otherwise difficult to observe.
Phylogenetic trees are the most common datatype by which we examine evolutionary patterns. However, biological and practical considerations require the exploration of other models. Here, we address a problem concerning the representation of conflicting and partially overlapping datasets in phylogenetics. We examine the problem of aligning many source trees from independent phylogenetic analyses into a structure that can be analyzed and synthesized but retain all of the original structure and source information. We present methods to map trees into a common graph structure using a graph database. This allows the information in the trees to be stored and synthesized in several ways. Specifically, we demonstrate how these graphs can be used to construct enormous trees as an alternative to labor-intensive grafting exercise and other methods that make the synthetic tree difficult to update. We also show how examination of the relationships in the graph allows patterns to emerge concerning support and information that are difficult to discern with existing methods. Because these methods scale well into the millions of nodes, these techniques should lead to the construction and maintenance of even larger phylogenies and new techniques for analyzing graphs that maintain the structure of the underlying trees.