To develop our methodology, we used data sets of treated and untreated cells or cells of a different type and we assumed this classification to be known. This enabled a basic quality assessment such that we should expect, after clustering the processed data, cells to partition into different clusters based on their known designation. We used principal component analysis to monitor our clustering expectation, calculated a matrix decomposition into singular values and plotted the first 2 components of the loadings.