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Reconciliation Revisited: Handling Multiple Optima When Reconciling with Duplication, Transfer, and Loss

  • Conference paper
Research in Computational Molecular Biology (RECOMB 2013)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7821))

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(mn 2) 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.

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Author information

Authors and Affiliations

  1. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, USA

    Mukul S. Bansal & Manolis Kellis

  2. Dept. of Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA

    Eric J. Alm

  3. Broad Institute of MIT and Harvard, Cambridge, USA

    Eric J. Alm & Manolis Kellis

Authors
  1. Mukul S. Bansal
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  2. Eric J. Alm
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  3. Manolis Kellis
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Editor information

Editors and Affiliations

  1. School of Mathematics, Peking University, Beijing, P.R. China

    Minghua Deng

  2. Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, 100084, Beijing, P.R. China

    Rui Jiang

  3. Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA

    Fengzhu Sun

  4. Department of Automation, Tsinghua University, P.O. Box, 100084, Beijing, China

    Xuegong Zhang

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Bansal, M.S., Alm, E.J., Kellis, M. (2013). Reconciliation Revisited: Handling Multiple Optima When Reconciling with Duplication, Transfer, and Loss. In: Deng, M., Jiang, R., Sun, F., Zhang, X. (eds) Research in Computational Molecular Biology. RECOMB 2013. Lecture Notes in Computer Science(), vol 7821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37195-0_1

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  • DOI: https://doi.org/10.1007/978-3-642-37195-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37194-3

  • Online ISBN: 978-3-642-37195-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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