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MGLEX - MetaGenome Likelihood EXtractor

Project description

This Python Package provides a probabilistic model to classify nucleotide sequences in metagenome samples. It was developed as a framework to help researchers to reconstruct individual genomes from such datasets using custom workflows and to give developers the possibility to integrate the model into their programs.


  • Integrates nucleotide composition, multi-sample coverage and taxonomic annotation

  • Learns a model in linear time with respect to the number of input sequences

  • Classifies novel sequences in linear time

  • Calculates likelihood and p-values

  • Calculates probabilistic distances between genome bins


This package was created using NumPy by Johannes Dröge at the Computational Biology of Infection Research Group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.

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