Analysis of GIBA filtering methods

We have tested the possible combinations of the 4 methods that compose the filtering process (density, haircut operation, best neighbor and cutting edge) in order to see how they affect the final results and how the function of one method affects the others.

We have chosen specific range of values for each method parameter:

for the density parameter:  0.55,  0.8

for the haircut operation parameter: 2 or 3

for the best neighbor parameter: 0.6,  0.75  and

for the cutting edge parameter: 0.6,  0.75

Choosing a parameter value out of the proposed range would be meaningless because the parameter method would become either too rigorous and it would produce very few clusters (if it was higher than the proposed maximum) or would add noise to the final data (if it was lower than the proposed minimum).

We have examined all possible combinations, using a parameter step of 0.5, in three datasets with different properties: 2 online database dataset (MIPS and DIP) and a dataset from individual experiment (Gavin_2006). So we have run 192 different filter combinations for each dataset.

Click here for the results of the analysis of GIBA filtering methods.

Click here for the datasets produced from the analysis of GIBA filtering methods.