Evidence map›Paper›PMID 26744021›Full record

ArticleBMC bioinformatics2016

Fast and accurate branch lengths estimation for phylogenomic trees.

Manuel Binet, Olivier Gascuel, Celine Scornavacca, Emmanuel J P Douzery, Fabio Pardi

Abstract read
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  6. Review
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  9. Phylogenomic branch length estimation using quartets.Bioinformatics (Oxford, England) · 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

5 authors.

Manuel BinetLaboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), CNRS, Université de Montpellier, Montpellier, France. binet@lirmm.fr.
Olivier GascuelLaboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), CNRS, Université de Montpellier, Montpellier, France. gascuel@lirmm.fr.
Celine ScornavaccaInstitut de Biologie Computationnelle, Montpellier, France. celine.scornavacca@umontpellier.fr.
Emmanuel J P DouzeryInstitut des Sciences de l'Evolution de Montpellier, CNRS, IRD, EPHE, Université de Montpellier, France. emmanuel.douzery@umontpellier.fr.
Fabio PardiLaboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), CNRS, Université de Montpellier, Montpellier, France. pardi@lirmm.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBranch lengths are an important attribute of phylogenetic trees, providing essential information for many studies in evolutionary biology. Yet, part of the current methodology to reconstruct a phylogeny from genomic information - namely supertree methods - focuses on the topology or structure of the phylogenetic tree, rather than the evolutionary divergences associated to it. Moreover, accurate methods to estimate branch lengths - typically based on probabilistic analysis of a concatenated alignment - are limited by large demands in memory and computing time, and may become impractical when the data sets are too large.

resultsHere, we present a novel phylogenomic distance-based method, named ERaBLE (Evolutionary Rates and Branch Length Estimation), to estimate the branch lengths of a given reference topology, and the relative evolutionary rates of the genes employed in the analysis. ERaBLE uses as input data a potentially very large collection of distance matrices, where each matrix is obtained from a different genomic region - either directly from its sequence alignment, or indirectly from a gene tree inferred from the alignment. Our experiments show that ERaBLE is very fast and fairly accurate when compared to other possible approaches for the same tasks. Specifically, it efficiently and accurately deals with large data sets, such as the OrthoMaM v8 database, composed of 6,953 exons from up to 40 mammals.

conclusionsERaBLE may be used as a complement to supertree methods - or it may provide an efficient alternative to maximum likelihood analysis of concatenated alignments - to estimate branch lengths from phylogenomic data sets.

Indexed as

PhylogenyAnimalsComputer SimulationDatabases, FactualGenomicsMammalsModels, MolecularSequence Alignment

Identifiers

PMID26744021
PMCPMC4705742

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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.