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Metabolomics requires a command of numerous tools, the outputs of which are typically integrated through in\u2010house 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.<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>\n                          We introduce\n                          <jats:italic>eCOMET<\/jats:italic>\n                          , 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.\n                        <\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>\n                          Our package combines metabolome feature metadata with quantification tables (e.g.\n                          <jats:italic>mzmine<\/jats:italic>\n                          ), feature dissimilarity matrices (e.g. modified cosine and\n                          <jats:italic>DreaMS<\/jats:italic>\n                          ), and feature annotations (e.g.\n                          <jats:italic>SIRIUS<\/jats:italic>\n                          ) into a cohesive R data object to facilitate downstream analyses, including the calculation of diversity and disparity metrics and differential accumulation analysis. We provide two tutorials, each explores herbivore\u2010induced\n                          <jats:italic>Arabidopsis thaliana<\/jats:italic>\n                          metabolome and 10 co\u2010occurring tropical trees species metabolomes.\n                        <\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>Our 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 into these fields.<\/jats:p>\n                      <\/jats:list-item>\n                    <\/jats:list>\n                  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