Evidence map›Paper›PMID 26209413›Full record

ArticleSystematic biology2015

PoMo: An Allele Frequency-Based Approach for Species Tree Estimation.

Nicola De Maio, Dominik Schrempf, Carolin Kosiol

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 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  8. Review
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  10. Evolutionary applications · 2023
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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

3 authors.

Nicola De MaioInstitut für Populationsgenetik, Vetmeduni Vienna, Wien 1210, Austria; Vienna Graduate School of Population Genetics, Wien, Austria; and Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7BN, UK.
Dominik SchrempfInstitut für Populationsgenetik, Vetmeduni Vienna, Wien 1210, Austria; Vienna Graduate School of Population Genetics, Wien, Austria; and.
Carolin KosiolInstitut für Populationsgenetik, Vetmeduni Vienna, Wien 1210, Austria; carolin.kosiol@vetmeduni.ac.at.

Funding

Austrian Science Fund FWF W 1225
6 · The paper itself

Abstract

Incomplete lineage sorting can cause incongruencies of the overall species-level phylogenetic tree with the phylogenetic trees for individual genes or genomic segments. If these incongruencies are not accounted for, it is possible to incur several biases in species tree estimation. Here, we present a simple maximum likelihood approach that accounts for ancestral variation and incomplete lineage sorting. We use a POlymorphisms-aware phylogenetic MOdel (PoMo) that we have recently shown to efficiently estimate mutation rates and fixation biases from within and between-species variation data. We extend this model to perform efficient estimation of species trees. We test the performance of PoMo in several different scenarios of incomplete lineage sorting using simulations and compare it with existing methods both in accuracy and computational speed. In contrast to other approaches, our model does not use coalescent theory but is allele frequency based. We show that PoMo is well suited for genome-wide species tree estimation and that on such data it is more accurate than previous approaches.

Indexed as

Computer SimulationGene FrequencyPhylogenyAnimalsClassificationHominidaeMutationPolymorphism, GeneticIncomplete lineage sortingPhylogeneticsPoMoSpecies tree

Identifiers

PMID26209413
PMCPMC4604832

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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.