eCOMET: An R package for evaluating metabolic diversity and enrichment from LC-MS/MS data to test ecological hypotheses from individuals to ecosystems
Min‐Soo ChoiiD, Dale L. ForristeriD, Guillaume J. DuryiD, Kyo Bin KangiD, Brian E. SedioiD, Youngsung JooiD
Abstract
O_LIMethods in metabolomics have grown exponentially in recent years, providing new insight into the ecological function and evolutionary impact of diverse plant metabolites. Metabolomics requires a command of numerous tools, the outputs of which are typically integrated through in-house, custom code that presents a workflow bottleneck and a barrier to entry for researchers in ecology, evolution, and behavior who may benefit from adding a metabolomics perspective to their research. C_LIO_LIWe introduce eCOMET, an R package for integrating and harmonizing the outputs of common metabolomics bioinformatics tools and conducting statistical analyses and data visualization methods useful for ecological metabolomics. C_LIO_LIOur package combines metabolome feature metadata with quantification tables (e.g., mzmine), feature dissimilarity matrices (e.g., modified cosine and DreaMS), and feature annotations (e.g., SIRIUS) into a cohesive R data object to facilitate downstream analyses, including the calculation of diversity and disparity metrics and differential accumulation analysis. C_LIO_LIOur goal is to make metabolomics accessible to a wider range of researchers in ecology, evolution, and behavior to unlock the potential of ecological metabolomics to generate novel insight in these fields. C_LI
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