ToppGene or any functional annotation-based prioritization method has some limitations. First, when using a training set of genes, the assumption is that the disease genes we have yet to discover will be consistent with what is already known about a disease and/or its genetic basis, which may not always be the case. Second, the annotations and analyses, as well as the prioritization, can only be as accurate as the underlying online sources from which the annotations are retrieved. Similar to functional annotation-based methods, the performance of network-based prioritization methods (ToppNet) is also dependent on the quality of interaction data, which currently suffers from incompleteness and unreliability with missing interactions and false positives.
