Skip to Main content Skip to Navigation
Journal articles

Accounting for ambiguity in ancestral sequence reconstruction

Abstract : Motivation: The reconstruction of ancestral genetic sequences from the analysis of contemporan-eous data is a powerful tool to improve our understanding of molecular evolution. Various statistical criteria defined in a phylogenetic framework can be used to infer nucleotide, amino-acid or codon states at internal nodes of the tree, for every position along the sequence. These criteria generally select the state that maximizes (or minimizes) a given criterion. Although it is perfectly sensible from a statistical perspective, that strategy fails to convey useful information about the level of uncertainty associated to the inference. Results: The present study introduces a new criterion for ancestral sequence reconstruction, the minimum posterior expected error (MPEE), that selects a single state whenever the signal conveyed by the data is strong, and a combination of multiple states otherwise. We also assess the performance of a criterion based on the Brier scoring scheme which, like MPEE, does not rely on any tuning parameters. The precision and accuracy of several other criteria that involve arbitrarily set tuning parameters are also evaluated. Large scale simulations demonstrate the benefits of using the MPEE and Brier-based criteria with a substantial increase in the accuracy of the inference of past sequences compared to the standard approach and realistic compromises on the precision of the solutions returned. Availability and implementation: The software package PhyML (https://github.com/stephaneguin don/phyml) provides an implementation of the Maximum A Posteriori (MAP) and MPEE criteria for reconstructing ancestral nucleotide and amino-acid sequences.
Complete list of metadatas

Cited literature [31 references]  Display  Hide  Download

https://hal-pasteur.archives-ouvertes.fr/pasteur-02404399
Contributor : Olivier Gascuel <>
Submitted on : Wednesday, December 11, 2019 - 12:21:17 PM
Last modification on : Wednesday, May 13, 2020 - 3:28:01 PM
Long-term archiving on: : Thursday, March 12, 2020 - 7:41:55 PM

Identifiers

Collections

Citation

Adrien Oliva, Sylvain Pulicani, Vincent Lefort, Laurent Brehelin, Olivier Gascuel, et al.. Accounting for ambiguity in ancestral sequence reconstruction. Bioinformatics, Oxford University Press (OUP), 2019, ⟨10.1093/bioinformatics/btz249⟩. ⟨pasteur-02404399⟩

Share

Metrics

Record views

201

Files downloads

294