Fig. 4: METRIC can correct the measurement error in assessed nutrient profiles on real data from MCTS (microbiome diet study)31. | Nature Communications

Fig. 4: METRIC can correct the measurement error in assessed nutrient profiles on real data from MCTS (microbiome diet study)31.

From: Microbiome-based correction for random errors in nutrient profiles derived from self-reported dietary assessments

Fig. 4

The Pearson’s Rank Correlation Coefficient \(\rho\) is adopted to evaluate the correlation across various types of nutrient profiles. All nutrient concentrations are in the unit of grams. All corrected/true values shown are the log of nutrient concentrations. a \({\rho }_{c}\) (i.e., \(\rho\) between corrected and true values) and \({\rho }_{a}\) (i.e., \(\rho\) between assessed and true values) decrease as the standard deviation of added Gaussian noise \(\sigma\) increases. Data are presented as mean values +/− standard error of the mean (SEM), derived from five training repeats (n = 5) for each case. All following panels focus on the case of \(\sigma\) = 1.0. b The correlation between assessed values and true values of log concentrations of carotene among different samples. c The correlation between corrected values (predictions of METRIC) and true values of log concentrations of carotene among different samples. d, e The similar comparison for octadecanoic acid shows a modest correction. f, g The similar comparison for fiber shows a strong correction. h The correction performance for all nutrients is measured by (\({\rho }_{c}-{\rho }_{a}\)). Source data are provided as a source data file.

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