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Fig. 2 | BMC Genomics

Fig. 2

From: Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population

Fig. 2

The influence of geography and BMI factors on the composition of the gut microbiome. A The box plots (box limits, upper and lower quartiles; center line, median; whiskers, 1.5 × interquartile range) show the alpha diversity assessed by the Shannon index of healthy and obese groups in five countries. Only in GER, the Shannon index of healthy people is significantly higher than that of obese people. (Wilcoxon rank-sum test, P < 0.05). B Principal coordinates analysis (PCoA) plot dependent on Bray–Curtis distances shows that obese (green) and healthy (red) people have essentially different gut microbiome profiles as PERMANOVA (R2 = 0.012, P = 0.001). Each point in the plot corresponds to one person. The ellipses correspond to the 95% confidence region. C The receiver operating characteristic (ROC) plots shows the classification effect of geographical factors on different countries by the Random Forest (RF) model. D The identical PCoA plot shows that the gut microbiome composition of people in different regions is significantly different (R2 = 0.051, P = 0.001). Each color in the plot corresponds to one country. Similarly, each point in the plot corresponds to one person

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