Multivariate and Multichannel Discrete Hidden Markov Models for Categorical Sequences

HMM-integrated Bayesian approach for detecting CNV and LOH events from single-cell RNA-seq data

Analysis of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH) in cancer

Fit hidden Markov models using Template Model Builder (TMB): flexible state-dependent distributions, transition probability structures, random effects, and smoothing splines.

Maximum likelihood analysis Of animal MovemENT behavior Using multivariate Hidden Markov Models

R package - Animal movement modelling using hidden Markov models

Full Bayesian Inference for Hidden Markov Models

Travel time prediction from GPS observations using an HMM

A local TU annotation tool for multi-sample comparison

Estimation of natural selection and allele age from time series allele frequency data using a novel likelihood-based approach

A stochastic epidemiological model that supplements the conventional reported cases with pooled samples from wastewater for assessing the overall SARS-CoV-2 burden at the community level.

A R-Shiny web interface that forecasts fuel prices based on historical data, using HMM.

An HMM-based domain caller from bw

Estimating temporally variable selection intensity from ancient DNA data with a combination of forward- and backward-in-time simulations

This demo showcases the main features and flexibility of the hmmTMB package in R, and how HMMs can be used in general.

Project to explore state space model inference including Kalman filters and hidden Markov models.

An R interface for dEploid. dEploid is designed for deconvoluting mixed genomes with unknown proportions. Traditional ‘phasing’ programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infe…

Generalized Pair Hidden Markov Chain Model (GPHMM)

Estimating temporally variable selection intensity from ancient DNA data

R scripts to iteratively generate Hidden Markov Models interactively (IIHMM) and automatically (AIHMM).