title: BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC.
abstract: BACKGROUND
  We have previously combined statistical alignment and phylogenetic footprinting to detect conserved functional elements without assuming a fixed alignment. Considering a probability-weighted distribution of alignments removes sensitivity to alignment errors, properly accommodates regions of alignment uncertainty, and increases the accuracy of functional element prediction. Our method utilized standard dynamic programming hidden markov model algorithms to analyze up to four sequences.
  
  
  RESULTS
  We present a novel approach, implemented in the software package BigFoot, for performing phylogenetic footprinting on greater numbers of sequences. We have developed a Markov chain Monte Carlo (MCMC) approach which samples both sequence alignments and locations of slowly evolving regions. We implement our method as an extension of the existing StatAlign software package and test it on well-annotated regions controlling the expression of the even-skipped gene in Drosophila and the alpha-globin gene in vertebrates. The results exhibit how adding additional sequences to the analysis has the potential to improve the accuracy of functional predictions, and demonstrate how BigFoot outperforms existing alignment-based phylogenetic footprinting techniques.
  
  
  CONCLUSIONS
  BigFoot extends a combined alignment and phylogenetic footprinting approach to analyze larger amounts of sequence data using MCMC. Our approach is robust to alignment error and uncertainty and can be applied to a variety of biological datasets. The source code and documentation are publicly available for download from http://www.stats.ox.ac.uk/~satija/BigFoot/
authors.affiliation: Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG Oxford, UK. satija@stats.ox.ac.uk
authors.forename: Rahul
authors.initials: R
authors.lastname: Satija
authors.forename: Adám
authors.initials: A
authors.lastname: Novák
authors.forename: István
authors.initials: I
authors.lastname: Miklós
authors.forename: Rune
authors.initials: R
authors.lastname: Lyngsø
authors.forename: Jotun
authors.initials: J
authors.lastname: Hein
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019143:Evolution, Molecular; D008390:Markov Chains; D008957:Models, Genetic