ArticlePloS one2015
Phylogenetic profiling: how much input data is enough?
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Comparative Genomics of Viral Genomes and Identification of Three Novel Viroporin-Like Superfamilies.Microbial physiology · 2026Article
- A Multi-level Perspective on the Evolution of Orthologs and Their Functions.Journal of molecular evolution · 2025Review
- ProTaxoVis-protein taxonomic visualisation of presence.BMC bioinformatics · 2025Article
- EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals.Nature communications · 2025Article
- Phylogenetic Profiling Analysis of the Phycobilisome Revealed a Novel State-Transition Regulator Gene in Synechocystis sp. PCC 6803.Plant & cell physiology · 2024Article
- Assembling bacterial puzzles: piecing together functions into microbial pathways.NAR genomics and bioinformatics · 2024Article
- A phylogenetic profiling approach identifies novel ciliogenesis genes in Drosophila and C. elegans.The EMBO journal · 2023Article
- Identifying protein function and functional links based on large-scale co-occurrence patterns.PloS one · 2022Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- Article
- Co-evolution based machine-learning for predicting functional interactions between human genes.Nature communications · 2021Article
- CladeOScope: functional interactions through the prism of clade-wise co-evolution.NAR genomics and bioinformatics · 2021Article
- The Distribution of Several Genomic Virulence Determinants Does Not Corroborate the Established Serotyping Classification ofInternational journal of molecular sciences · 2021Article
- The Functional Classification of ORF8 in SARS-CoV-2 Replication, Immune Evasion, and Viral Pathogenesis Inferred through Phylogenetic Profiling.Evolutionary bioinformatics online · 2021Article
- Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways.Frontiers in molecular biosciences · 2021Review
- Characterizing human genomic coevolution in locus-gene regulatory interactions.BioData mining · 2019Article
- The evolutionary signal in metagenome phyletic profiles predicts many gene functions.Microbiome · 2018Article
- Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.Bioinformatics (Oxford, England) · 2018Article
- Solar-panel and parasol strategies shape the proteorhodopsin distribution pattern in marine Flavobacteriia.The ISME journal · 2018Article
- Modules of co-occurrence in the cyanobacterial pan-genome reveal functional associations between groups of ortholog genes.PLoS genetics · 2018Article
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2 authors.
Funding
Abstract
Phylogenetic profiling is a well-established approach for predicting gene function based on patterns of gene presence and absence across species. Much of the recent developments have focused on methodological improvements, but relatively little is known about the effect of input data size on the quality of predictions. In this work, we ask: how many genomes and functional annotations need to be considered for phylogenetic profiling to be effective? Phylogenetic profiling generally benefits from an increased amount of input data. However, by decomposing this improvement in predictive accuracy in terms of the contribution of additional genomes and of additional annotations, we observed diminishing returns in adding more than ∼ 100 genomes, whereas increasing the number of annotations remained strongly beneficial throughout. We also observed that maximising phylogenetic diversity within a clade of interest improves predictive accuracy, but the effect is small compared to changes in the number of genomes under comparison. Finally, we show that these findings are supported in light of the Open World Assumption, which posits that functional annotation databases are inherently incomplete. All the tools and data used in this work are available for reuse from http://lab.dessimoz.org/14_phylprof. Scripts used to analyse the data are available on request from the authors.
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