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- W3088469545 abstract "Joint analysis of microbiome and metabolomic data represents an imperative objective as the field moves beyond basic microbiome association studies and turns towards mechanistic and translational investigations. We present a censored Gaussian graphical model framework, where the metabolomic data are treated as continuous and the microbiome data as censored at zero, to identify direct interactions (defined as conditional dependence relationships) between microbial species and metabolites. Simulated examples show that our method metaMint performs favorably compared to the existing ones. metaMint also provides interpretable microbe-metabolite interactions when applied to a bacterial vaginosis data set. R implementation of metaMint is available on GitHub." @default.
- W3088469545 created "2020-10-01" @default.
- W3088469545 creator A5001130484 @default.
- W3088469545 date "2020-09-21" @default.
- W3088469545 modified "2023-10-03" @default.
- W3088469545 title "Joint Microbial and Metabolomic Network Estimation with the Censored Gaussian Graphical Model" @default.
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- W3088469545 doi "https://doi.org/10.1007/s12561-020-09294-z" @default.
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