Evidence map›Paper›PMID 25503772›Full record

ArticleSystematic biology2015

Genetic distance for a general non-stationary markov substitution process.

Benjamin D Kaehler, Von Bing Yap, Rongli Zhang, Gavin A Huttley

Abstract read
In one paragraph

Article in Systematic biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Benjamin D KaehlerJohn Curtin School of Medical Research, Australian National University, Canberra, ACT, 2600, Australia; and.
Von Bing YapDepartment of Statistics and Applied Probability, National University of Singapore, Singapore, 117546, Singapore.
Rongli ZhangDepartment of Statistics and Applied Probability, National University of Singapore, Singapore, 117546, Singapore.
Gavin A HuttleyJohn Curtin School of Medical Research, Australian National University, Canberra, ACT, 2600, Australia; and gavin.huttley@anu.edu.au ben.kaehler@anu.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The genetic distance between biological sequences is a fundamental quantity in molecular evolution. It pertains to questions of rates of evolution, existence of a molecular clock, and phylogenetic inference. Under the class of continuous-time substitution models, the distance is commonly defined as the expected number of substitutions at any site in the sequence. We eschew the almost ubiquitous assumptions of evolution under stationarity and time-reversible conditions and extend the concept of the expected number of substitutions to nonstationary Markov models where the only remaining constraint is of time homogeneity between nodes in the tree. Our measure of genetic distance reduces to the standard formulation if the data in question are consistent with the stationarity assumption. We apply this general model to samples from across the tree of life to compare distances so obtained with those from the general time-reversible model, with and without rate heterogeneity across sites, and the paralinear distance, an empirical pairwise method explicitly designed to address nonstationarity. We discover that estimates from both variants of the general time-reversible model and the paralinear distance systematically overestimate genetic distance and departure from the molecular clock. The magnitude of the distance bias is proportional to departure from stationarity, which we demonstrate to be associated with longer edge lengths. The marked improvement in consistency between the general nonstationary Markov model and sequence alignments leads us to conclude that analyses of evolutionary rates and phylogenies will be substantively improved by application of this model.

Indexed as

Evolution, MolecularModels, GeneticAnimalsHumansMammalsMarkov ChainsPhylogenygenetic distanceMarkov processmaximum likelihoodmolecular clocknonstationary

Identifiers

PMID25503772
PMCPMC4380038

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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 OpenQuestion graph.