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Methods Mol Biol. 2019;1910:149-175. doi: 10.1007/978-1-4939-9074-0_5.

Inferring Orthology and Paralogy.

Altenhoff AM1,2, Glover NM2,3,4, Dessimoz C5,6,7,8,9.

Author information

1
Computer Science Department, ETH Zurich, Zurich, Switzerland.
2
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
3
Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
4
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
5
Swiss Institute of Bioinformatics, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
6
Department of Computational Biology, University of Lausanne, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
7
Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland. Christophe.Dessimoz@unil.ch.
8
Department of Genetics, Evolution and Environment, University College 6 London, London, UK. Christophe.Dessimoz@unil.ch.
9
Department of Computer Science, University College London, London, UK. Christophe.Dessimoz@unil.ch.

Abstract

The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments.

KEYWORDS:

Orthology; Orthology benchmarking; Paralogy; Tree reconciliation

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