Flow cytometry (FCM) allows scientists to rapidly quantify up to 50 parameters for millions of cells per sample. The bottleneck in the application of the technology is data analysis, and the high number of parameters measured by the current generation of instruments requires the use of advanced computational algorithms to make full use of their capabilities. This review summarizes the main steps of FCM data analysis, focusing on the use of the most recent bioinformatic tools developed for an R‐based programming environment. In particular, for each stage of the data analysis, libraries and packages currently available are listed, and a brief description of their functioning is included.