Extended documentation can be found on the website: https://lynettecaitlin.github.io/oHMMed/
The oHMMed package contains an implementation of Hidden Markov Models
with ordered hidden states and emission densities
(https://doi.org/10.1186/s12859-024-05751-4). More precisely: We
assume a sequence of un-observable (’hidden’) variables with discrete
categories known as states. Moving along this sequence, the probability
of a specific state occurring at any step depends only on the state
preceding it. Each hidden variable along the sequence produces/’emits’
an observable data point. We assume that these emitted data points are
distributed according to some continuous distribution (currently: normal
or gamma-poisson compound) with state-specific parameters. Further, we
assume that the continuous emission distributions per state are
parameterised so that they can be ordered by increasing mean. In fact,
transitions between states in the hidden sequence can only occur between
states that emit densities that are neighbours in the ordering by mean.
Given the observed data sequence, our models assign each part of the
hidden sequence to a state, and infer the transition rates between them
as well as the parameters of the state-specific emission distributions.
This is the general framework of oHMMed (ordered Hidden Markov Model
with emission densities), and it can be applied to any system that
fulfills these assumptions.
Mathematical details and graphical representations of the algorithms can be found in the following article: https://biorxiv.org/cgi/content/short/2023.06.26.546495v1
The corresponding genome annotation results from this paper can be found at:
https://github.com/LynetteCaitlin/oHMMed/blob/main/Data/GenomeAnnotations.zip
You can install the latest stable cran version using (recommended):
install.packages("oHMMed")In order to install the latest stable development version from GitHub you can use:
# install.packages("devtools")
devtools::install_github("LynetteCaitlin/oHMMed@*release")The development version can be installed using:
# install.packages("devtools")
devtools::install_github("LynetteCaitlin/oHMMed")Please read the following usage recommendations: https://github.com/LynetteCaitlin/oHMMed/blob/main/UsageRecommendations.pdf
The accompanying R scripts are:
-
for the case of normal emission densities: https://github.com/LynetteCaitlin/oHMMed/blob/main/simulation_scripts/MCMC_normal_sims.R
-
and for gamma-poisson emission densities: https://github.com/LynetteCaitlin/oHMMed/blob/main/simulation_scripts/MCMC_gamma-poisson_sims.R
Template code for viewing summaries of oHMMed diagnostics, and for
viewing the results of two different sequence annotations side-by-side
and assessing associations/correlations between them can be found at:
https://github.com/LynetteCaitlin/oHMMed/blob/main/simulation_scripts/oHMMedOutputAnalyses.R
Lynette Caitlin Mikula (Algorithm development, usage, and application)
Claus Vogl (Algorithm development)
Michal Majka (R technicalities and code optimisation) - PACKAGE MAINTAINER