Title
Shrinkage Effect in Ancestral Maximum Likelihood
Abstract
Ancestral maximum likelihood (AML) is a method that simultaneously reconstructs a phylogenetic tree and ancestral sequences from extant data (sequences at the leaves). The tree and ancestral sequences maximize the probability of observing the given data under a Markov model of sequence evolution, in which branch lengths are also optimized but constrained to take the same value on any edge across all sequence sites. AML differs from the more usual form of maximum likelihood (ML) in phylogenetics because ML averages over all possible ancestral sequences. ML has long been know to be statistically consistent - that is, it converges on the correct tree with probability approaching 1 as the sequence length grows. However, the statistical consistency of AML has not been formally determined, despite informal remarks in a literature that dates back 20 years. In this short note we prove a general result that implies that AML is statistically inconsistent. In particular we show that AML can 'shrink' short edges in a tree, resulting in a tree that has no internal resolution as the sequence length grows. Our results apply to any number of taxa.
Year
DOI
Venue
2009
10.1109/TCBB.2008.107
Computational Biology and Bioinformatics, IEEE/ACM Transactions
Keywords
Field
DocType
Markov processes,bioinformatics,genetics,maximum likelihood estimation,molecular biophysics,Markov model,ancestral maximum likelihood,ancestral sequences,branch lengths,maximum likelihood estimation,phylogenetic tree,sequence evolution,shrinkage effect,Biology and genetics,Markov processes
Combinatorics,Phylogenetic tree,Markov process,Biology,Markov model,Markov chain,Maximum likelihood,Bioinformatics,Statistics,Phylogenetics,Computational complexity theory,Constrained optimization
Journal
Volume
Issue
ISSN
6
1
1545-5963
Citations 
PageRank 
References 
0
0.34
5
Authors
3
Name
Order
Citations
PageRank
Elchanan Mossel11725145.16
Sébastien Roch241041.27
Mike Steel327041.87