ArticleApplications in plant sciences
Data-driven guidelines for phylogenomic analyses using SNP data.
Article in Applications in plant sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.Journal of medical Internet research · 2026Article
- Drought Response and Genetic Variation in Scots Pine Seedlings' Provenances: Insights From High-Throughput Phenotyping for Climate-Resilient Forestry.Evolutionary applications · 2025Article
- Data-driven guidelines for phylogenomic analyses using SNP data.Applications in plant sciencesArticle
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Premise: There is a general lack of consensus on the best practices for filtering of single-nucleotide polymorphisms (SNPs) and whether it is better to use SNPs or include flanking regions (full "locus") in phylogenomic analyses and subsequent comparative methods. Methods: Using genotyping-by-sequencing data from 22 Results: Our results revealed five aspects of phylogenomic data usage that may be generally applicable: (1) tree topology is largely congruent across analyses; (2) filtering strictly for SNP retention (e.g., 90-100%) reduces support and can alter some inferred relationships; (3) absolute branch lengths vary by two orders of magnitude between SNP and locus datasets; (4) data type and branch length variation have little effect on divergence time estimation; and (5) phylograms alter the estimation of ancestral states and rates of morphological evolution. Discussion: Using SNP or locus datasets does not alter phylogenetic inference significantly, unless researchers want or need to use absolute branch lengths. We recommend against using excessive filtering thresholds for SNP retention to reduce the risk of producing inconsistent topologies and generating low support.
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