Analysis with Profile Hidden Markov Models
Import profile hidden Markov models into R.
Iterative model refinement.
Deconstruct an alignment.
The Viterbi algorithm.
Sequence weighting.
Export profile hidden Markov models as text.
Multiple sequence alignment in R.
The aphid package for analysis with profile hidden Markov models.
The backward algorithm.
Derive a standard hidden Markov model from a set of sequences.
Derive a profile hidden Markov model from sequences.
The forward algorithm.
Generate random sequences from a model.
Sum of logged probabilities.
Optimized profile HMM construction.
Plot standard hidden Markov models.
Plot profile hidden Markov models.
Posterior decoding.
Print summary methods.
Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Useful links