Flow cytometry is a widely used technique for the detection and quantification of low frequency or rare cell populations at limits of detection (LOD) of 0.1% or lower, such as circulating tumour cells and haematopoietic stem cells. An increasing number of computational tools are available for automated gating of flow cytometry data. These tools have the capability to eliminate operator variation from traditional manual gating. Nevertheless, the potential for variation in data outputs arising from analysis of the same dataset using different algorithms means that research is needed to define the confidence in the use of automated data analysis software platforms for identifying rare cell populations.