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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

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The Kernel of Maximum Agreement Subtrees.

Krister M Swenson¹, Eric Chen, Nicholas D Pattengale

¹Department of Mathematics and Statistics, University of Ottawa and the Laboratoire de Combinatoire et d'Informatique Mathématique-LaCIM at the Université du Québec à Montréal-UQAM, 8337 Ave. Casgrain, Montreal, QC H2P2K7, Canada. akswenson@uottawa.ca

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|January 11, 2012

Summary

This summary is machine-generated.

We introduce the Kernel Agreement SubTree (KAST) to summarize common structures across multiple Maximum Agreement SubTrees (MASTs). KAST offers a reliable consensus method for phylogenetic analysis, addressing limitations of individual MASTs.

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A Practical Guide to Phylogenetics for Nonexperts

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Area of Science:

Computational Biology
Phylogenetics
Data Analysis

Background:

Maximum Agreement SubTree (MAST) identifies the largest common subtree in a set of trees, summarizing shared substructure.
Individual MASTs can be misleading due to their potential exponential number and lack of shared leaves, necessitating a more robust consensus method.

Purpose of the Study:

Introduce the Kernel Agreement SubTree (KAST) as a summary of common substructure across all MASTs.
Establish KAST as a reliable measure of confidence in tree sets and a method to discern common phylogenetic structure.
Evaluate KAST's performance against other consensus methods using Bayesian analysis of flatworm genomes.

Main Methods:

Define and introduce the concept of Kernel Agreement SubTree (KAST).
Develop a polynomial-time algorithm for calculating KAST, particularly for trees with bounded degrees.
Apply KAST to analyze competing phylogenetic hypotheses and compare its trend with other consensus methods on flatworm genome data.

Main Results:

Demonstrate that KAST can be calculated in polynomial time for trees with bounded degrees.
Showcase KAST's utility in discerning common phylogenetic structure and measuring confidence in tree sets.
Present a comparative analysis of KAST's trend against other consensus methods using real genomic data.

Conclusions:

KAST provides a more stable and informative summary of common substructure compared to individual MASTs.
KAST serves as a valuable tool for assessing confidence in phylogenetic analyses and understanding evolutionary relationships.
The study validates KAST's effectiveness through its application in a Bayesian analysis of flatworm genomes.