AC-PCoA: Adjustment for confounding factors using principal coordinate analysis
Fig 3
Results of MBQC data (Dataset ‘A’).
A: Two-dimensional representations colored by specimens after conducting PCoA, AC-PCoA and aPCoA using Euclidean distance and Bray-Curtis distance. B: MANOVA F-statistic, NMI of k-means clustering, and classification accuracy. Specimens are set to be the true labels. MANOVA, k-means clustering, and classification were conducted on two and three principal coordinates from PCoA, AC-PCoA, and aPCoA.