title: A hierarchical model for incomplete alignments in phylogenetic inference.
abstract: BACKGROUND
  Full-length DNA and protein sequences that span the entire length of a gene are ideally used for multiple sequence alignments (MSAs) and the subsequent inference of their relationships. Frequently, however, MSAs contain a substantial amount of missing data. For example, expressed sequence tags (ESTs), which are partial sequences of expressed genes, are the predominant source of sequence data for many organisms. The patterns of missing data typical for EST-derived alignments greatly compromise the accuracy of estimated phylogenies.
  
  
  RESULTS
  We present a statistical method for inferring phylogenetic trees from EST-based incomplete MSA data. We propose a class of hierarchical models for modeling pairwise distances between the sequences, and develop a fully Bayesian approach for estimation of the model parameters. Once the distance matrix is estimated, the phylogenetic tree may be constructed by applying neighbor-joining (or any other algorithm of choice). We also show that maximizing the marginal likelihood from the Bayesian approach yields similar results to a profile likelihood estimation. The proposed methods are illustrated using simulated protein families, for which the true phylogeny is known, and one real protein family.
  
  
  BACKGROUND
  R code for fitting these models are available from: http://people.bu.edu/gupta/software.htm.
authors.affiliation: Department of Mathematics, Illinois State University, Normal, IL, USA.
authors.forename: Fuxia
authors.initials: F
authors.lastname: Cheng
authors.forename: Stefanie
authors.initials: S
authors.lastname: Hartmann
authors.forename: Mayetri
authors.initials: M
authors.lastname: Gupta
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
authors.forename: Todd J
authors.initials: TJ
authors.lastname: Vision
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D020224:Expressed Sequence Tags; D015233:Models, Statistical; D010802:Phylogeny; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods