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bioRxiv · 10.1101/611418

DreamDMI: a tool for Disease Module Identification in molecular networks

Tomasoni, M.·Choobdar, S.·Marbach, D.·Gomez, S.·Crawford, J.·Zhang, W.·Bergmann, S.
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Abstract

SummaryWe define a disease module as a partition of a molecular network whose components are jointly associated with one or several diseases or risk factors thereof. Identification of such modules, across different types of networks, has great potential for elucidating disease mechanisms and establishing new powerful bio-markers. To this end, we launched the \"Disease Module Identification (DMI) DREAM Challenge\", a community effort to build and evaluate unsupervised molecular network modularisation algorithms (Choobdar et al., 2018). Here we present MONET, a toolbox providing easy and unified access to the three top methods from the DMI DREAM Challenge for the bioinformatics community.\n\nAvailability and ImplementationMONET is a command line tool for Linux, based on Docker and Singularity containers; the core algorithms were written in R, Python, Ada and C++. It is freely available for download at https://github.com/BergmannLab/MONET.git\n\nContactmattia.tomasoni@unil.ch (MT); sven.bergmann@unil.ch (SB)

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Tomasoni, M., Choobdar, S., Marbach, D., Gomez, S., Crawford, J., Zhang, W., Bergmann, S.. 2019-05-07. DreamDMI: a tool for Disease Module Identification in molecular networks. https://doi.org/10.1101/611418

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