Principal Component Analysis (PCA) graph for telomeric association data. The two first principal components are plotted with the proportion of variance explained by each component printed next to the axis labels. A- Relative frequencies of each association type: the graph clearly shows that most of the variance can be attributed to two types of associations: pp and pqloop; B- Probabilities of telomeric associations by type: most of the variance can be attributed to pqloop frequency.
Mompart et al. BMC Cell Biology 2013 14:30 doi:10.1186/1471-2121-14-30