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bioRxiv · 10.64898/2026.06.02.729701

eCOMET: An R package for evaluating metabolic diversity and enrichment from LC-MS/MS data to test ecological hypotheses from individuals to ecosystems

Choi, M.-S.·Forrister, D. L.·Dury, G. J.·Kang, K. B.·Sedio, B. E.·Joo, Y.
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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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Choi, M.-S., Forrister, D. L., Dury, G. J., Kang, K. B., Sedio, B. E., Joo, Y.. 2026-06-05. eCOMET: An R package for evaluating metabolic diversity and enrichment from LC-MS/MS data to test ecological hypotheses from individuals to ecosystems. https://doi.org/10.64898/2026.06.02.729701

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