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

Affiliation

Station d'Ecologie Théorique et Expérimentale de Moulis, CNRS, Moulis, France. [Email]

Abstract

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.

Keywords

Low similarity segments,Multiple sequence alignment,Phylogeny,Positive selection,Primary sequence error,Profile hidden Markov models,