**2.5 Clustering**

Cluster analysis techniques have proven to be helpful to understand gene expression data by uncovering unknown relationships among genes and unveiling different subtypes of diseases when it comes to clustering biological samples [10]. In the following section, we present methods for sample-based and gene-based clustering, starting with traditional methods used after data transformation then model-based clustering for data generated using a combination of probability distributions (**Figure 3**).
