AmpliPhy improves gene trees by adding homologous sequences without affecting alignments

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ID: 324410
2026
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Abstract
Abstract Motivation In phylogenomics, gene tree reconstruction depends on multiple sequence alignment and tree inference, and ongoing work continues to improve inference quality. Denser taxon sampling has been associated with improved gene tree inference, suggesting that adding homologs could be a practical route to higher accuracy as sequence databases continue to expand. However, adding sequences can influence multiple steps of typical inference pipelines, and little is known on its specific effect on the multiple sequence alignment, tree reconstruction, and rooting steps. Results We performed a large-scale empirical and simulated benchmarks to quantify how homolog enrichment affects alignment and phylogenetic inference. Using an enrichment–impoverishment design and a measure of tree accuracy based on taxonomic congruence, we found that enrichment consistently improves tree inference quality, while effects on alignment quality are marginal. We show that this improvement is associated with, but not restricted to accurate root placement on enriched trees when sensitive homolog search is accompanied. Notably, much of the benefit can be retained with relatively compact alignments produced by sequence addition. Building on these observations, we provide a tool, AmpliPhy, which efficiently improves phylogenetic reconstruction of protein families through homolog enrichment. Availability and Implementation The AmpliPhy open-source pipeline software is available at https://github.com/DessimozLab/ampliphy. The scripts used to generate the data and figures are available from https://github.com/DessimozLab/ampliphy-analysis.
Reference Key
openalex_W7201963775 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Dongwook Kim, Manuel Gil, Kazutaka Katoh, Christophe Dessimoz
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Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag222
URL
https://doi.org/10.1093/bioadv/vbag222
Keywords Keywords not found

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