In the last 10 years, a tremendous progress characterized flow cytometry in its different aspects. In particular, major advances have been conducted regarding the hardware/instrumentation and reagent development, thus allowing fine cell analysis up to 20 parameters. As a result, this technology generates very complex datasets that demand for the development of optimal tools of analysis. Recently, many independent research groups approached the problem by using both supervised and unsupervised methods. In this article, we will review the new developments concerning the use of bioinformatics for polychromatic flow cytometry and propose what should be done to unravel the enormous heterogeneity of the cells we interrogate each day.