HaMMLET – Fast Bayesian Hidden Markov Model with Wavelet Compression

HaMMLET

:: DESCRIPTION

HaMMLET is a fast Forward-Backward Gibbs sampler for Bayesian inference on Hidden Markov Models (HMM). It uses the Haar wavelet transform to dynamically compress the data based on the current variance sample in each iteration.

::DEVELOPER

Schliep lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • GCC

:: DOWNLOAD

 HaMMLET

:: MORE INFORMATION

Citation

Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression.
Wiedenhoeft J, Brugel E, Schliep A.
PLoS Comput Biol. 2016 May 13;12(5):e1004871. doi: 10.1371/journal.pcbi.1004871.

Exit mobile version