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A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Maximum Likelihood Phylogenetic Inference is Consistent on Multiple Sequence Alignments, with or without Gaps.

Jakub Truszkowski¹, Nick Goldman²

¹European Molecular Biology Laboratory, European Bioinformatics Institute Wellcome Genome Campus, Hinxton, CB10 1SD, UK; Cancer Research UK Cambridge Institute, University of Cambridge Robinson Way, Cambridge CB2 0RE, UK jakubt@ebi.ac.uk.

Systematic Biology

|November 29, 2015

Summary

This summary is machine-generated.

Maximum likelihood phylogenetic inference is statistically consistent for gapped alignments. This method accurately recovers evolutionary trees, even with missing data, refuting prior suggestions of inconsistency.

Keywords:

Kullback–Leibler divergence maximum likelihood missing data multiple sequence alignment phylogeny

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Last Updated: Mar 29, 2026

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Published on: February 5, 2014

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Published on: August 16, 2017

Area of Science:

Computational Biology
Phylogenetics
Bioinformatics

Background:

Phylogenetic inference aims to reconstruct evolutionary history.
Maximum likelihood (ML) is a common method for phylogenetic inference.
The statistical consistency of ML with gapped alignments has been debated.

Purpose of the Study:

To investigate the statistical consistency of maximum likelihood phylogenetic inference on gapped multiple sequence alignments (MSAs).
To address concerns about the potential inconsistency of ML when gaps are treated as missing data.
To provide a rigorous mathematical proof for the consistency of ML in phylogenetics.

Main Methods:

Mathematical proof of consistency for gapped MSAs under specific assumptions.
Analysis of asymptotic behavior of maximum likelihood estimation.
Derivation of a new proof for the consistency of ML on ungapped alignments.

Main Results:

Maximum likelihood phylogenetic inference is statistically consistent on gapped MSAs when substitution rates are positive.
ML asymptotically recovers the true tree with edge lengths reflecting the mean number of substitutions per site.
The study refutes the suggestion that ML is inconsistent with gapped data when gaps are treated as missing.

Conclusions:

Maximum likelihood is a statistically sound method for phylogenetic inference, even with gapped alignments.
The findings validate the use of ML in reconstructing evolutionary relationships from sequence data.
This work clarifies theoretical underpinnings of phylogenetic methods in bioinformatics.