Skip to main content
Figure 1 | BMC Bioinformatics

Figure 1

From: Probabilistic principal component analysis for metabolomic data

Figure 1

Results of fitting a PPCA model to the urine dataset. A. Plot of the modified BIC values and the proportion of variation explained by each model: the higher the BIC value the better the model. B. The scores plot: the red triangles denote the subjects in the treatment group and the black dots denote those in the control group. The grey ellipses are the 95% posterior sets indicating the uncertainty associated with each estimated score. C. A barplot of spectral bins with loadings which are significantly different from zero and greater in absolute value than 0.8. The barplot shows how the selected spectral regions load on PC 1 and their corresponding 95% confidence intervals.

Back to article page