Reconciliation revisited: handling multiple optima when reconciling with duplication, transfer, and loss

Authors:
Mukul S. Bansal;Eric J. Alm;Manolis Kellis
Affiliations:
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge;Dept. of Biological Engineering, Massachusetts Institute of Technology, Cambridge and Broad Institute of MIT and Harvard, Cambridge;Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge and Broad Institute of MIT and Harvard, Cambridge
Venue:
RECOMB'13 Proceedings of the 17th international conference on Research in Computational Molecular Biology
Year:
2013

Citing 8
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Efficient algorithms for the reconciliation problem with gene duplication, horizontal transfer and loss

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Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees

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Abstract

Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While Duplication-Loss (DL) reconciliation leads to a unique maximum-parsimony solution, Duplication-Transfer-Loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult the infer the true evolutionary history of the gene family. Here, we present an effective, efficient, and scalable method for dealing with this fundamental problem in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn2) time, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mapping and event assignments, and to investigate the impact of varying event costs.