BIG-PI [10 (link),12 (link),13 (link)], GPI-SOM [15 (link)], FragAnchor [17 (link)] and MemType-2L [18 (link)] web server predictors were interrogated to test our datasets, while DGPI [14 ] was run locally with the last free available distribution. When testing BIG-PI, which implements different parameterizations for the different kingdoms, the suitable predictor was used for each protein.
Four parameters were used to evaluate the prediction performances. We indicated with TP and TN the number of True Positive and True Negative predictions, respectively, and with FP and FN the number of False Positive and False Negative predictions, respectively.
The Coverage, or true positive rate, was calculated as the number of proteins correctly predicted as GPI-anchored over the total number of positive examples.
Cov=TPTP+FN
The Accuracy value corresponds to the number of proteins correctly predicted as GPI-anchored over the total number of protein predicted as GPI-anchored.
Acc=TPTP+FP
The false positive rate corresponds to the number of protein predicted as GPI-anchored but annotated as negative examples over the total number of negative examples.
The Matthews Correlation Coefficient was calculated as:
MCC=TPTNFPFN(TP+FP)(TP+FN)(TN+FP)(TN+FN)
A thorough explanation of the purposes of these indexes can be found in [24 (link)].
Free full text: Click here