Evidence map›Paper›PMID 24764459›Full record

ArticleBioinformatics (Oxford, England)2014

kdetrees: Non-parametric estimation of phylogenetic tree distributions.

Grady Weyenberg, Peter M Huggins, Christopher L Schardl, Daniel K Howe, Ruriko Yoshida

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Pangenome-Wide Association Study in theInternational journal of molecular sciences · 2024
    Article
  2. Tukey's Depth for Object Data.Journal of the American Statistical Association · 2023
    Article
  3. Article
  4. Article
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  11. Reticulation, divergence, and the phylogeography-phylogenetics continuum.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  12. Clustering Genes of Common Evolutionary History.Molecular biology and evolution · 2016
    Article
  13. Article
  14. Distances Between Extension Spaces of Phylogenetic Trees.IEEE transactions on computational biology and bioinformatics
    Article
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.

Grady WeyenbergDepartment of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.
Peter M HugginsDepartment of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.
Christopher L SchardlDepartment of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.
Daniel K HoweDepartment of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.
Ruriko YoshidaDepartment of Statistics, University of Kentucky, Lexington, KY 40536, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, Plant Pathology Department and Department of Veterinary Science, University of Kentucky, Lexington, KY 40546, USA.

Funding

Geometry of gene cophylogenies as relates to genome evolution and speciationR01GM086888 · NIGMS · UNIVERSITY OF KENTUCKY · PI YOSHIDA, RURIKO · 2008 to 2012
$1.4M
NIGMS NIH HHS R01 GM086888NIGMS NIH HHS R01GM086888
6 · The paper itself

Abstract

motivationAlthough the majority of gene histories found in a clade of organisms are expected to be generated by a common process (e.g. the coalescent process), it is well known that numerous other coexisting processes (e.g. horizontal gene transfers, gene duplication and subsequent neofunctionalization) will cause some genes to exhibit a history distinct from those of the majority of genes. Such 'outlying' gene trees are considered to be biologically interesting, and identifying these genes has become an important problem in phylogenetics.

resultsWe propose and implement kdetrees, a non-parametric method for estimating distributions of phylogenetic trees, with the goal of identifying trees that are significantly different from the rest of the trees in the sample. Our method compares favorably with a similar recently published method, featuring an improvement of one polynomial order of computational complexity (to quadratic in the number of trees analyzed), with simulation studies suggesting only a small penalty to classification accuracy. Application of kdetrees to a set of Apicomplexa genes identified several unreliable sequence alignments that had escaped previous detection, as well as a gene independently reported as a possible case of horizontal gene transfer. We also analyze a set of Epichloë genes, fungi symbiotic with grasses, successfully identifying a contrived instance of paralogy. AVAILABILITY AND IMPLEMENTATION: Our method for estimating tree distributions and identifying outlying trees is implemented as the R package kdetrees and is available for download from CRAN.

Indexed as

PhylogenyAlgorithmsApicomplexaEpichloeGenesGene Transfer, HorizontalSequence AlignmentSoftwareStatistics, Nonparametric

Identifiers

PMID24764459
PMCPMC4176058

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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.