diHMM v0.1 beta

:: DESCRIPTION

diHMM (Hierarchical Hidden Markov Model) is a novel computational method for finding chromatin states at multiple scales. The model takes as input a multidimensional set of histone modifications for several cell types and classifies the genome into a preselected number of nucleosome-level and domain-level hidden states.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

• Linux/Windows/MacOsX
• Matlab

:: DOWNLOAD

diHMM

:: MORE INFORMATION

Citation

Marco E, Meuleman W, Huang J, Glass K, Pinello L, Wang J, Kellis M, Yuan GC.
Multi-scale chromatin state annotation using a hierarchical hidden Markov model.
Nature Communications. 2017 Apr 7;8:15011.