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BMC BioinformaticsBioinformaticsPeer-reviewed journal article

AMON: Annotation of metabolite origins via networks to better integrate microbiome and metabolome data

M. Shaffer, Kumar ThurimellaiD, Kevin D. QuinniD, Katrina Doenges, Xuhong ZhangiD, Samantha S. Bokatzian, Nichole A. ReisdorphiD, Catherine LozuponeiD

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Abstract

MotivationUntargeted metabolomics of host-associated samples has yielded insights into mechanisms by which microbes modulate health. However, data interpretation is challenged by the complexity of origins of the small molecules measured, which can come from the host, microbes that live with the host, or from other exposures such as diet or the environment.\n\nResultsWe address this challenge through development of AMON: Annotation of Metabolite Origins via Networks. AMON is an open-source bioinformatics application that can be used to determine the degree to which annotated compounds in the metabolome may have been produced by bacteria present, the host, either (i.e. both the bacteria and host are capable of production), or neither (i.e. neither the human or the fecal microbiome are predicted to be capable of producing the observed metabolite).\n\nAvailability and ImplementationThis software is available at https://github.com/lozuponelab/AMON as well as via pip.\n\nContactcatherine.lozupone@ucdenver.edu

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