RASCAL: A Randomized Approach for Coevolutionary Analysis

Abstract

A popular method for coevolutionary inference is cophylogenetic reconstruction where the branch length of the phylogenies have been previously derived. This approach, unlike the more generalized reconstruction techniques that are NP-Hard, can reconcile the shared evolutionary history of a pair of phylogenetic trees in polynomial time. This approach, while proven to be highly successful, requires a high polynomial running time. This is quickly becoming a limiting factor of this approach due to the continual increase in size of coevolutionary data sets. One existing method that combats this issue proposes a trade-off of accuracy for an asymptotic time complexity reduction. This technique in almost 70% of cases converges on Pareto optimal solutions in linear time. We build on this prior work by proposing an alternate linear time algorithm (RASCAL) that offers a significant accuracy increase, with RASCAL converging on Pareto optimal solutions in 85% of cases and unlike prior methods can ensure, with high probability, that all optimal solutions can be recovered, provided sufficient replicates are performed.

paco: implementing Procrustean Approach to Cophylogeny in R

“…; Conow et al . ; Balbuena, Míguez‐Lozano & Blasco‐Costa ; Drinkwater & Charleston ). These tools can be typically classified as either event‐based or global‐fit methods (Desdevises ; Balbuena, Míguez‐Lozano & Blasco‐Costa ).…”

“…It is now feasible to use event‐based approaches for large datasets thanks to recent advances that significantly reduce their computational cost (Drinkwater & Charleston ; Libeskind‐Hadas et al . ; Drinkwater & Charleston ). Conversely, global‐fit approaches assess the degree of congruence between two phylogenies and some can also identify the specific interactions (or links) that contribute most to their concordance (Legendre, Desdevises & Bazin ; Desdevises ; Balbuena, Míguez‐Lozano & Blasco‐Costa ).…”

“…TREEMAP, ParaFit, Jane, PACo, RASCAL) currently available to assess phylogenetic congruence between interacting species (e.g. Charleston & Page 2002;Legendre, Desdevises & Bazin 2002;Hommola et al 2009;Conow et al 2010;Balbuena, M ıguez-Lozano & Blasco-Costa 2013;Drinkwater & Charleston 2016). These tools can be typically classified as either event-based or globalfit methods (Desdevises 2007;Balbuena, M ıguez-Lozano & Blasco-Costa 2013).…”

“…Event-based methods map one evolutionary tree to the other, based on either edges or nodes, with the aim of understanding the underlying evolutionary processes, particularly coevolutionary associations (Conow et al 2010;Drinkwater & Charleston 2014). It is now feasible to use eventbased approaches for large datasets thanks to recent advances that significantly reduce their computational cost (Drinkwater & Charleston 2014;Libeskind-Hadas et al 2014;Drinkwater & Charleston 2016). Conversely, global-fit approaches assess the degree of congruence between two phylogenies and some can also identify the specific interactions (or links) that contribute most to their concordance (Legendre, Desdevises & Bazin 2002;Desdevises 2007;Balbuena, M ıguez-Lozano & Blasco-Costa 2013).…”

A geography aware reconciliation method to investigate diversification patterns in host/parasite interactions

“…transfers cannot occur towards a node in the host phylogeny that has already split into child species at the time of the transfer event) (Merkle & Middendorf 2005; Nojgaard et al 2017). This constraint is explicit in Mowgli (Doyon et al 2011; Doyon et al 2010), ecceTera (Jacox et al 2016) and RASCAL (Drinkwater & Charleston 2016). Hence, reconciliation methods have greatly improved in the last decade; algorithms are now efficient and some have solved the time consistency issue that affected some of the first methodological developments in the field.…”