ReviewMolecular biology and evolution2012
Statistics and truth in phylogenomics.
Review in Molecular biology and evolution, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
92 citing papers in PubMed.
- Phylogenetic Accuracy Under Non-stationary and Non-homogeneous Conditions: A Simulation Study.Systematic biology · 2026Article
- Phylogenomic subsampling and upsampling for efficient evolutionary analyses of big data.Molecular biology and evolution · 2026Article
- Phylogenomic subsampling and upsampling for efficient evolutionary analyses of big data.bioRxiv : the preprint server for biology · 2026Article
- Evidence for Cryptic Sex in Escovopsis, a Mycoparasite in the Fungus-Growing Ant Symbiosis.Genome biology and evolution · 2026Article
- The genetic foundations of convergent traits.Nature reviews. Genetics · 2026Review
- Phenotypic complexity determines the predictability of molecular convergence.bioRxiv : the preprint server for biology · 2026Article
- Phylogenomics of Marine Angelfishes: Diagnosing Sources of Systematic Discordance for an Iconic Reef Fish Family (F: Pomacanthidae).Systematic biology · 2025Article
- Article
- MEGA12: Molecular Evolutionary Genetic Analysis Version 12 for Adaptive and Green Computing.Molecular biology and evolution · 2024Article
- The Meaning and Measure of Concordance Factors in Phylogenomics.Molecular biology and evolution · 2024Review
- Article
- Article
- Article
- Discovering Fragile Clades and Causal Sequences in Phylogenomics by Evolutionary Sparse Learning.Molecular biology and evolution · 2024Article
- Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses.Systematic biology · 2024Article
- Assessing sequence heterogeneity in Chlorellaceae DNA barcode markers for phylogenetic inference.Journal, genetic engineering & biotechnology · 2023Article
- Chromosome-Aware Phylogenomics of Assassin Bugs (Hemiptera: Reduvioidea) Elucidates Ancient Gene Conflict.Molecular biology and evolution · 2023Article
- Likelihood-Based Tests of Species Tree Hypotheses.Molecular biology and evolution · 2023Article
- Article
- Divergence and introgression among theEvolution letters · 2022Article
32 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Phylogenomics refers to the inference of historical relationships among species using genome-scale sequence data and to the use of phylogenetic analysis to infer protein function in multigene families. With rapidly decreasing sequencing costs, phylogenomics is becoming synonymous with evolutionary analysis of genome-scale and taxonomically densely sampled data sets. In phylogenetic inference applications, this translates into very large data sets that yield evolutionary and functional inferences with extremely small variances and high statistical confidence (P value). However, reports of highly significant P values are increasing even for contrasting phylogenetic hypotheses depending on the evolutionary model and inference method used, making it difficult to establish true relationships. We argue that the assessment of the robustness of results to biological factors, that may systematically mislead (bias) the outcomes of statistical estimation, will be a key to avoiding incorrect phylogenomic inferences. In fact, there is a need for increased emphasis on the magnitude of differences (effect sizes) in addition to the P values of the statistical test of the null hypothesis. On the other hand, the amount of sequence data available will likely always remain inadequate for some phylogenomic applications, for example, those involving episodic positive selection at individual codon positions and in specific lineages. Again, a focus on effect size and biological relevance, rather than the P value, may be warranted. Here, we present a theoretical overview and discuss practical aspects of the interplay between effect sizes, bias, and P values as it relates to the statistical inference of evolutionary truth in phylogenomics.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.