RAP is a rank aggregation-based data fusion approach for gene prioritization in plants. It can be used to perform the gene prioritization in Arabidopsis thaliana and 28 non-plant species.
ChroMoS (Chromatin Modified SNPs) combines genetic and epigenetic data to facilitate SNP classification, prioritization and prediction of their functional effect.
maxLRc is a likelihood ratio-based measure for the statistical component of ranking rare variants under a case-control study design that avoids the hypothesis-testing paradigm.
EPSILON is an extendable framework for eQTL prioritization, which mitigates the effect of highly connected genes and unreliable interactions by constructing a local network before a network-based similarity measure is applied to select the true causal gene.
NetworkPrioritizer provides multiple features to rank individual nodes based on centrality measures according to their relevance to the rest of the network. This can be accomplished either globally or locally with regard to a set of seed nodes. The global approach is basically a standard centrality analysis, whereas the local approach reveals how important individual nodes are for the connections between the set of seed nodes and the rest of the network. A frequent application of NetworkPrioritizer is the prioritization of candidate disease genes. Here, genes known for a given disease constitute the seed set, and the nodes top-ranked as a result of applying NetworkPrioritizer are identified as promising putative disease genes. NetworkPrioritizer can be applied to both directed and undirected networks. It will, however, treat all edges as undirected for the centrality computations. Apart from the computation of centrality measures NetworkPrioritizer also offers useful tools for the comparison and aggregation of multiple rankings.
Endeavour is a software application for the computational prioritization of candidates genes, based on a set of training genes. It is made up of three stages: training, scoring and fusion. In the first stage, information about the training genes (genes already known to play a role in the process under study) are retrieved from numerous data sources in order to build models. It includes functionnal annotations, protein-protein interactions, regulatory information, expression data, sequence based data and literature mining data. In the second stage, the models are then used to score the candidate genes and to rank them according to their scores. Lastly, the rankings per data source are fused into a global ranking using order statistics. Endeavour is available for human, mouse, rat, fruit fly and worm.
FlyNet is a network prioritization server for the Drosophila melanogaster biology. The FlyNet web server is specialized for the generation of versatile hypothesis in Drosophila-based studies.