Evidence map›Paper›PMID 22759416›Full record

ArticleBMC bioinformatics2012

Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence.

Ruchi Chaudhary, J Gordon Burleigh, Oliver Eulenstein

Abstract read
In one paragraph

Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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0cells of the map it votes in
9citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Asymmetric Cluster-Based Measures for Comparative Phylogenetics.Journal of computational biology : a journal of computational molecular cell biology · 2024
    Article
  2. Article
  3. Non-parametric correction of estimated gene trees using TRACTION.Algorithms for molecular biology : AMB · 2020
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. DrML: probabilistic modeling of gene duplications.Journal of computational biology : a journal of computational molecular cell biology · 2014
    Article
  9. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ruchi ChaudharyDepartment of Computer Science, Iowa State University, Ames, IA 50011, USA.
J Gordon Burleigh
Oliver Eulenstein

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results.

resultsWe introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n2 for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses.

conclusionsThe new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.

Indexed as

AlgorithmsEvolution, MolecularGene DuplicationComputational BiologyGenomeGenomicsModels, TheoreticalPhylogenyYeasts

Identifiers

PMID22759416
PMCPMC3382437

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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.