Alternative clustering algorithms of adult AML cohort. (A) A multidimensional scatterplot generated using principal component analysis (PCA) reduces the dimensionality of the data by projecting the expression data matrix into 3 dimensions. The largest sources of gene expression signal variance are represented as principal components (labeled PC1, PC2, PC3).⁵²  (B) Two-dimensional unsupervised clustering dendrograms and “heat map” of gene expression data from the 170 AML cases using 9463 genes. Pearson correlation coefficient was used to compute gene and patient similarity. The cluster-to-cluster distance was computed using the average linkage. The relative gene expression scale is depicted on the left with the normalized scores ranging from –5 to more than 5. Gene cluster and patient cluster dendrograms are plotted to the top and right sides of the heat map, respectively. After PCA and hierarchical clustering was performed, the individual patients were color coded for comparison with their VxInsight cluster membership. These methods showed a significant degree of concordance with VxInsight cluster membership (adjusted Rand index = 0.3457, P < .001) (Table S15).⁴⁴