The expected values for the reference distribution are generated by taking the mean PORGS values from bootstrapping the proximity matrix.
Simulated data were used to validate the PORGS method by comparing the known distribution of data points with optimal partitions and group membership obtained from the model.
Using the PORGS method, we partitioned the proximity matrix into optimal group membership for k = 1 to n groups by minimizing the cost function (Eq.
Next we applied PORGS to genetic data derived from Chinook salmon populations.
Comparison of PORGS method with standard genetic methods
To compare results obtained by the PORGS method with those from a standard hierarchical approach to clustering genetic data, the unweighted pair-group method using arithmetic averages (UPGMA) was applied to both the simulated and Chinook salmon data sets to generate a tree with PHYLIP software (Felsenstein, 1989).
When PORGS was applied to the simulated data, the first partition (k=2) occurred between P4 and P5 (Fig.
Figure 3A shows a vertical dashed line drawn to intersect branches that correspond to the three main clusters identified in the PORGS analysis.
Compared with random set partitions, PORGS reduces the number of cost function evaluations by eliminating redundant cluster combinations.
I'm a great animal lover, and I do believe that animals have an individual personality unto themselves, and that personality is in a sense brought out by the owner," said Scanlan, whose team created practical, life-like puppet porgs that were then animated by a team of VFX artists to give their animatronic bodies flight and movement.