ArticleG3 (Bethesda, Md.)2014
Correcting for sequencing error in maximum likelihood phylogeny inference.
Article in G3 (Bethesda, Md.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Rate variation and recurrent sequence errors in pandemic-scale phylogenetics.Nature methods · 2026Article
- Noise leads to the perceived increase in evolutionary rates over short time scales.PLoS computational biology · 2024Article
- SUP: a probabilistic framework to propagate genome sequence uncertainty, with applications.NAR genomics and bioinformatics · 2023Article
- Bayesian Inference of Ancestral Host-Parasite Interactions under a Phylogenetic Model of Host Repertoire Evolution.Systematic biology · 2020Article
- Maximize Resolution or Minimize Error? Using Genotyping-By-Sequencing to Investigate the Recent Diversification ofFrontiers in plant science · 2019Article
- Phylogeny-guided (meta)genome mining approach for the targeted discovery of new microbial natural products.Journal of industrial microbiology & biotechnology · 2017Review
- Article
- Computing tumor trees from single cells.Genome biology · 2016Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate phylogenies are critical to taxonomy as well as studies of speciation processes and other evolutionary patterns. Accurate branch lengths in phylogenies are critical for dating and rate measurements. Such accuracy may be jeopardized by unacknowledged sequencing error. We use simulated data to test a correction for DNA sequencing error in maximum likelihood phylogeny inference. Over a wide range of data polymorphism and true error rate, we found that correcting for sequencing error improves recovery of the branch lengths, even if the assumed error rate is up to twice the true error rate. Low error rates have little effect on recovery of the topology. When error is high, correction improves topological inference; however, when error is extremely high, using an assumed error rate greater than the true error rate leads to poor recovery of both topology and branch lengths. The error correction approach tested here was proposed in 2004 but has not been widely used, perhaps because researchers do not want to commit to an estimate of the error rate. This study shows that correction with an approximate error rate is generally preferable to ignoring the issue.
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Registered trials
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