Background: Horizontal gene transfer (HGT), a process of acquisition and fixation of foreign genetic material, is an important biological phenomenon. Several approaches to HGT inference have been proposed. However, most of them either rely on approximate, non-phylogenetic methods or on the tree reconciliation, which is computationally intensive and sensitive to parameter values. Results: We investigate the locus tree inference problem as a possible alternative that combines the advantages of both approaches. We present several algorithms to solve the problem in the parsimony framework. We introduce a novel tree mapping, which allows us to obtain a heuristic solution to the problems of locus tree inference and duplication classification. Conclusions: Our approach allows for faster comparisons of gene and species trees and improves known algorithms for duplication inference in the presence of polytomies in the species trees. We have implemented our algorithms in a software tool available at https://github.com/mciach/LocusTreeInference.
机构:
Univ Michigan, Dept Human Genet, Ann Arbor, MI 48109 USA
Univ Michigan, Ctr Computat Med & Biol, Ann Arbor, MI 48109 USA
Univ Michigan, Inst Life Sci, Ann Arbor, MI 48109 USAUniv Michigan, Dept Human Genet, Ann Arbor, MI 48109 USA
Rosenberg, Noah A.
Tao, Randa
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Univ Michigan, Ctr Computat Med & Biol, Ann Arbor, MI 48109 USAUniv Michigan, Dept Human Genet, Ann Arbor, MI 48109 USA
机构:
Univ Michigan, Museum Zool, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USAUniv Michigan, Museum Zool, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USA
Knowles, L. Lacey
Carstens, Bryan C.
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Univ Michigan, Museum Zool, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USAUniv Michigan, Museum Zool, Dept Ecol & Evolutionary Biol, Ann Arbor, MI 48109 USA