Statistically Consistent k-mer Methods for Phylogenetic Tree Reconstruction

Frequencies of k-mers in sequences are sometimes used as a basis for inferring phylogenetic trees without first obtaining a multiple sequence alignment. We show that a standard approach of using the squared Euclidean distance between k-mer vectors to approximate a tree metric can be statistically in...

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Bibliographic Details
Published in:Journal of computational biology Vol. 24; no. 2; p. 153
Main Authors: Allman, Elizabeth S, Rhodes, John A, Sullivant, Seth
Format: Journal Article
Language:English
Published: United States 01.02.2017
Subjects:
Algorithms
Base Sequence
Computer Simulation
Evolution, Molecular
Models, Genetic
Phylogeny
Sequence Alignment
Sequence Analysis, DNA
k-mer
phylogenetic trees
alignment-free methods
ISSN:1557-8666, 1557-8666
Online Access:Get more information
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Summary:Frequencies of k-mers in sequences are sometimes used as a basis for inferring phylogenetic trees without first obtaining a multiple sequence alignment. We show that a standard approach of using the squared Euclidean distance between k-mer vectors to approximate a tree metric can be statistically inconsistent. To remedy this, we derive model-based distance corrections for orthologous sequences without gaps, which lead to consistent tree inference. The identifiability of model parameters from k-mer frequencies is also studied. Finally, we report simulations showing that the corrected distance outperforms many other k-mer methods, even when sequences are generated with an insertion and deletion process. These results have implications for multiple sequence alignment as well since k-mer methods are usually the first step in constructing a guide tree for such algorithms.
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ISSN:1557-8666
1557-8666
DOI:10.1089/cmb.2015.0216