Clade IV appears to be the largest and most diverse cluster of Arabidopsis and rice subtilisin-like proteins.
MT2, MT1, CCL9, CCL8, ECM1, and SLC39A4 represent a diverse cluster of two metallothionein proteins, two macrophage proteins, one extracellular matrix protein, and one zinc transporter protein.
It is possible that the adenosquamous phenotype contributes to the observed early signature, but the uniform clustering of early tumors vs. the more diverse clustering of adenosquamous tumors suggests a temporal rather than a histological signature for this cluster.
However, these previous studies detected positive selection acting during the more distant evolutionary history of this locus to produce a diverse cluster of paralogous genes apparently established early in mammalian evolution [ 9, 10].
Also, many genes may be grouped into diverse clusters (or none of them) depending on their participation in different biological processes within the cell [ 13].
CAP and CPV are inversely related but imperfectly as CPV varies with cluster size even among similarly diverse clusters; a plot of CAP values against CPV values is shown in Figure 6 figure supplement 2. The CCI is calculated as the average number of genes per genome as a percentage of the total number of phams in that cluster.
Whilst it is too early to provide any concrete recommendations from these preliminary results, particularly given the questionable reliability of the social media data, the emergence of these diverse clusters might begin to shed light on the shifting spatio-temporal distributions of crime and their potential victims.
The origin of this 16S rRNA variation is unknown but could be revealed by more in-depth analyses of a greater number and range of coccolithophore species as well as analysis of genomic variation in some of the diverse clusters [ 36].
Eshghi et al. [ 29] and Gelbard et al. [ 13] also showed a lack of consistency across clustering techniques in the number of subgroups detected in real datasets in a comparison of diverse clustering techniques.
While the rapidly expanding resource of microarray data is currently analyzed primarily using diverse clustering techniques, methods for the analysis of network-type data describing interrelations of genes and proteins are less mature, and methods for joint analysis of the two data types are in nascent stage.
