Evaluating the usefulness of alignment filtering methods to reduce the impact of errors on evolutionary inferences

Arnaud Di Franco (1) , Raphaël Poujol (2) , Denis Baurain (3) , Herve Philippe (1, 2)

1 SETE - Station d'écologie théorique et expérimentale
2 Centre Robert Cedergren, Depatement Biochimie
3 InBioS PhytoSYST Eukaryot Phylogen

Background: Multiple Sequence Alignments (MSAs) are the starting point of molecular evolutionary analyses. Errors in MSAs generate a non-historical signal that can lead to incorrect inferences. Therefore, numerous efforts have been made to reduce the impact of alignment errors, by improving alignment algorithms and by developing methods to filter out poorly aligned regions. However, MSAs do not only contain alignment errors, but also primary sequence errors. Such errors may originate from sequencing errors, from assembly errors, or from erroneous structural annotations (such as incorrect intron/exon boundaries). Even though their existence is acknowledged, the impact of primary sequence errors on evolutionary inference is poorly characterized.

Mots clés: Phylogeny; Primary sequence error; Low similarity segments; Profile hidden Markov models; Multiple sequence alignment; Positive selection

Domaines: Sciences du Vivant [q-bio]; Bio-Informatique, Biologie Systémique [q-bio.QM]; Sciences de l'environnement

Arnaud Di Franco, Raphaël Poujol, Denis Baurain, Herve Philippe. Evaluating the usefulness of alignment filtering methods to reduce the impact of errors on evolutionary inferences. BMC Evolutionary Biology, 2019, 19 (1), ⟨10.1186/s12862-019-1350-2⟩. ⟨hal-02414477⟩