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Phylogenomic datasets invariably contain undetected stretches of non-homologous characters due to poor-quality sequences or erroneous gene models. The large-scale multi-gene nature of these datasets renders impractical or impossible detailed manual curation of sequences, but few tools exist that can automate this task. To address this issue, we developed a new method that takes as input a set of unaligned homologous sequences and uses an explicit probabilistic approach to identify and mask regions with non-homologous adjacent characters. These regions are defined as sharing no statistical support for homology with any other sequence in the set, which can result from e.g. sequencing errors or gene prediction errors creating frameshifts. Our methodology is implemented in the program PREQUAL, which is a fast and accurate tool for high-throughput filtering of sequences. The program is primarily aimed at amino acid sequences, although it can handle protein coding DNA sequences as well. It is fully customizable to allow fine-tuning of the filtering sensitivity.

PREQUAL: detecting non-homologous characters in sets of unaligned homologous sequences