GMMs offer several advantages over other clustering methods like k-means. Firstly, GMMs can model clusters of different shapes and sizes, while k-means assumes spherical clusters. Secondly, GMMs provide probabilistic assignments to clusters, which can be useful for uncertainty quantification. This is particularly important in cancer research where data variability is high.
