Cell assemblies, i.e., concurrently active groups of neurons, likely underlie neural processing for higher brain functions. Recent technological progress has enabled large-scale recording of neuronal activity, permitting the exploration and analysis of cell assembly dynamics. This review aims to provide both conceptual insights and practical knowledge pertaining to principal methodologies used for detecting cell assemblies in the last 13 years. The goal is to assist readers in comparing and selecting various protocols to optimize their data processing and analysis pipeline. Each algorithm is explained with its fundamental principles, their application in neuroscience for cell assembly detection, and illustrated with published studies. Recognizing the similarities, advantages, and drawbacks of diverse methodologies may pave the way for developing new procedures for cell assembly identification to facilitate future endeavors in the understanding of brain activity.