The aim of this paper is to present an overview of six independent computational methods for the selection and prioritization of candidate genes for human diseases and, rather than selecting a best method, to offer the prospective user a better understanding of the inputs, outputs and functionality of each available method. A survey of these methods also offers the bioinformatics community an opportunity to assess the efficacy of current computational approaches to disease gene identification, and informs future directions for research in this field.