The ability to gather genome-wide expression data is a computationally complex task. The human brain with its limitations cannot solve the problem. However, data can be fine-grained to an easily comprehensible level by subdividing the genes into a smaller number of categories and then analyzing them.
The goal of clustering is to subdivide a set of genes in such a way that similar items fall into the same cluster, whereas dissimilar items fall into different clusters. The important questions to be considered are decisions on similarity and usage for the items that have been clustered. Here we shall explore clustering genes and samples using the photoreceptor time series for the two genotypes.
