Running stochhmm

StochHMM implements standard HMM, HMM with duration (for viterbi algorithm) and in the future will implement hidden semi-Markov model architectures and algorithms. It grants researchers the power to integrate additional datasets in their HMM to improve predictions. Finally, it adapts HMM algorithms to provide stochastic decoding giving researchers the ability to explore and rank sub-optimal predictions.

To run the StochHMM command-line application you'll need a model file and a sequence. A couple example model files have been provided.

3_16_Eddy.hmm - GC rich model from Problem 3.16 of "Problems and Solutions in Biological Sequence Analysis. M. Borodovsky and S. Ekisheva. Cambridge Press, UK (2006)"

Dice.hmm - Dishonest Casino Dice model from pg 65 of "Biological Sequence Analysis: Probabilistic models of proteins and nucleic acids. R Durbin, S. Eddy, A. Krogh, and G. Mitchison. Cambridge Press, UK (1998)"

GC-skew.hmm - SkewR model for predicting R-loop forming regions in the human genome. See

The command-line options are as follows:

###Required command-line options and files

-model import model file -seq import sequence file in fasta format

###Non-stochastic Decoding:  Different algorithms available for decoding

-viterbi performs viterbi traceback -posterior Calculates posterior probabilities If no output options are supplied, this will return the posterior scores for all of the states.

-threshold <score>: Return only the States with a GFF_DESC, if they are
		greater than or equal to the threshold amount.

-nbest performs n-best viterbi algorithm

###Stochastic Decoding:

-stochastic Types: forward performs stochastic traceback using forward algorithm viterbi performs stochastic traceback using modified-viterbi algorithm posterior performs stochastic traceback using posterior algorithm -rep

###Output options:

-gff prints path in GFF format -path prints state path according to state number -label prints state path as labels

$ stochhmm -model ../examples/Dice.hmm -seq ../examples/Dice.fa -viterbi -label
$ stochhmm -model ../examples/3_16Eddy.hmm -seq ../example/3_16Eddy.fa -viterbi -gff
$ stochhmm -model ../examples/3_16Eddy.hmm -seq ../example/3_17Eddy.fa -posterior
$ stochhmm -model ../examples/Dice.hmm -seq ../examples/Dice.fa -stochastic viterbi -rep 10 -label
$ stochhmm -model ../examples/Dice.hmm -seq ../examples/Dice.fa -stochastic posterior -rep 10 -label