Extended Data Fig. 4: Performance for random Forest regression and classification on microbiome functional potential in predicting fasting measurements, total cholesterol and triglycerides in different lipoproteins.

The figure shows the performance of both RF regression and classification tasks trained on microbiome gene families profiles in predicting (a) the fasting measurements presented in Fig. 4a, sorted as in Fig. 4a. b, Predicting performances of the total cholesterol and (c) of triglycerides in different sizes of lipoproteins. For each lipoprotein, we considered its concentration values at both fasting and postprandial (6 h), and also the difference (rise) between the post-prandial concentration and the fasting one. Box plots show the distribution of the Spearman correlations (left axis) between real and predicted values using RF regression. Box plots show first and third quartiles (boxes) and the median (middle line), whiskers extends up-to 1.5× the interquartile range. Circles show the median AUC (right axis) of RF classification in predicting the bottom quartile of the distribution vs. the top quartile.