A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases <s> Evaluation of Gene Prioritization Tools <s> Despite increasing sequencing capacity, genetic disease investigation still frequently results in the identification of loci containing multiple candidate disease genes that need to be tested for involvement in the disease. This process can be expedited by prioritizing the candidates prior to testing. Over the last decade, a large number of computational methods and tools have been developed to assist the clinical geneticist in prioritizing candidate disease genes. In this chapter, we give an overview of computational tools that can be used for this purpose, all of which are freely available over the web. <s> BIB001 </s> A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases <s> Evaluation of Gene Prioritization Tools <s> Motivation: Gene prioritization aims at identifying the most promising candidate genes among a large pool of candidates—so as to maximize the yield and biological relevance of further downstream validation experiments and functional studies. During the past few years, several gene prioritization tools have been defined, and some of them have been implemented and made available through freely available web tools. In this study, we aim at comparing the predictive performance of eight publicly available prioritization tools on novel data. We have performed an analysis in which 42 recently reported disease-gene associations from literature are used to benchmark these tools before the underlying databases are updated. ::: ::: Results: Cross-validation on retrospective data provides performance estimate likely to be overoptimistic because some of the data sources are contaminated with knowledge from disease-gene association. Our approach mimics a novel discovery more closely and thus provides more realistic performance estimates. There are, however, marked differences, and tools that rely on more advanced data integration schemes appear more powerful. ::: ::: Contact: yves.moreau@esat.kuleuven.be ::: ::: Supplementary information: Supplementary data are available at Bioinformatics online. <s> BIB002 </s> A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases <s> Evaluation of Gene Prioritization Tools <s> In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly an ... <s> BIB003
Although some individual tools may demonstrate superior performance on average, none of them outperform in all cases BIB002 ,  , BIB003 , BIB001 . This may happen because of the different capability of methods to model aspects relevant to the disease mechanism, or due to the usage of distinct validation approaches and different training and testing datasets. In this chapter, we discuss approaches for validation of gene prioritization results, measures of performance, and their advantages and disadvantages.