viterbi.hmm: Computes the Viterbi path for a hidden markov model

In drramki-chop/edm: Scalable workflow to identify copy Number variants from exome sequencing data

Description

Estimates the most likely path for a hidden Markov Chain using the maximum likelihood Viterbi algorithm.

Usage

viterbi.hmm(transitions, loglikelihood, positions, expected.CNV.length)

Arguments

transitions	Transition matrix
loglikelihood	numeric matrix containing the loglikelihood of the data under the possible states
positions	Positions of the exons
expected.CNV.length	Expected length of CNV calls, which has an impact on the transition matrix between CNV states.

Details

Standard forward-backward Viterbi algorithm using a precomputed matrix of likelihoods.

Value

comp1	Description of 'comp1'
comp2	Description of 'comp2'

Author(s)

Vincent Plagnol

drramki-chop/edm documentation built on June 6, 2020, 8:48 a.m.