The accurate detection of cell-type specific DNA methylation alterations in the context of general epigenome studies is an important task to improve our understanding of epigenomics in disease development. Although a number of statistical algorithms designed to address this problem have emerged, the task remains challenging. Here we show that a recent commentary by Rahmani et al, that aims to address misconceptions and best practices in the field, continues to suffer from critical misconceptions in how statistical algorithms should be compared and evaluated. In addition, we report contradictory results on real EWAS datasets.