Variance stabilization and clustering after rlog transformation. Two transformations were applied to the counts of the Hammer et al.  dataset: the logarithm of normalized counts plus a pseudocount, i.e. f(K
+1), and the rlog. The gene-wise standard deviation of transformed values is variable across the range of the mean of counts using the logarithm (A), while relatively stable using the rlog (B). A hierarchical clustering on Euclidean distances and complete linkage using the rlog (D) transformed data clusters the samples into the groups defined by treatment and time, while using the logarithm-transformed counts (C) produces a more ambiguous result. sd, standard deviation.