Expansion of datasets for functional enrichment analyses by clustering
As outlined above, our example dataset generated a relatively small number of significantly regulated proteins, which limits the power of functional enrichment analyses. To expand the set of proteins for such analyses we performed non-biased k-means clustering, which resulted in effectively segregating 37 of the total 42 significantly regulated proteins into one of two clusters, which essentially correspond to up-regulated (cluster 6) and down-regulated (cluster 1) groups of proteins. Cluster 1 was larger and more inclusive, including 20 of the 21 down-regulated proteins and 185 non-significant proteins showing the same overall abundance pattern. Cluster 6 contained 17 of 21 up-regulated proteins and 37 non-significant proteins with a similar overall abundance pattern (Figure 4).