Evidence map›Paper›PMID 19046431›Full record

ArticleBMC bioinformatics2008

Comparison of methods for estimating the nucleotide substitution matrix.

Maribeth Oscamou, Daniel McDonald, Von Bing Yap, Gavin A Huttley, Manuel E Lladser, Rob Knight

Abstract readComparative Study
In one paragraph

Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Maribeth OscamouDepartment of Applied Mathematics, University of Colorado, Boulder, CO, USA. Maribeth.Oscamou@colorado.edu
Daniel McDonald
Von Bing Yap
Gavin A Huttley
Manuel E Lladser
Rob Knight

Funding

Trace the flow of genes in the gut microbiome of obese and lean twin pairsP01DK078669 · NIDDK · WASHINGTON UNIVERSITY · PI GORDON, JEFFREY I · 2007 to 2018
$16.0M
NIDDK NIH HHS P01 DK078669
6 · The paper itself

Abstract

backgroundThe nucleotide substitution rate matrix is a key parameter of molecular evolution. Several methods for inferring this parameter have been proposed, with different mathematical bases. These methods include counting sequence differences and taking the log of the resulting probability matrices, methods based on Markov triples, and maximum likelihood methods that infer the substitution probabilities that lead to the most likely model of evolution. However, the speed and accuracy of these methods has not been compared.

resultsDifferent methods differ in performance by orders of magnitude (ranging from 1 ms to 10 s per matrix), but differences in accuracy of rate matrix reconstruction appear to be relatively small. Encouragingly, relatively simple and fast methods can provide results at least as accurate as far more complex and computationally intensive methods, especially when the sequences to be compared are relatively short.

conclusionBased on the conditions tested, we recommend the use of method of Gojobori et al. (1982) for long sequences (> 600 nucleotides), and the method of Goldman et al. (1996) for shorter sequences (< 600 nucleotides). The method of Barry and Hartigan (1987) can provide somewhat more accuracy, measured as the Euclidean distance between the true and inferred matrices, on long sequences (> 2000 nucleotides) at the expense of substantially longer computation time. The availability of methods that are both fast and accurate will allow us to gain a global picture of change in the nucleotide substitution rate matrix on a genomewide scale across the tree of life.

Indexed as

Evolution, MolecularAlgorithmsComputational BiologyComputer SimulationData Interpretation, StatisticalDNADNA Mutational AnalysisLogistic ModelsMarkov ChainsModels, GeneticNucleotidesPhylogenyReproducibility of ResultsSensitivity and SpecificityDNANucleotides

Identifiers

PMID19046431
PMCPMC2655096

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Registered trials

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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.