SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays

Hit selection from high-throughput assays remains a critical bottleneck in realizing the potential of omic-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs. The specific limitations of these individual approaches and the lack of a systematic way by which to integrate their rankings have contributed to limited overlap in the reported results from comparable genome-wide studies and costly inefficiencies in secondary validation efforts. Using comparative analysis of parallel independent studies as a benchmark, we characterize the specific complementary contributions of each approach and demonstrate an optimal framework to integrate these methods. We describe selection by iterative pathway group and network analysis looping (SIGNAL), an integrated, iterative approach that uses both pathway and network methods to optimize gene prioritization. SIGNAL is accessible as a rapid user-friendly web-based application (https://signal.niaid.nih.gov). A record of this paper’s transparent peer review is included in the Supplemental information [Display omitted] •Using two cutoffs to segment omics data outperforms single cutoffs in hit selection•Pathway enrichment and network analysis provide contrasting solutions and trade-offs•Iterative selection by pathway, then network analysis, shows improved performance•Hit selection by this iterative method can be done rapidly using the SIGNAL website Choosing optimal cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions is all associated with critical analytical trade-offs when selecting candidates from high-throughput assays. We describe SIGNAL, a hit selection analysis platform that prioritizes candidates from omics data by using two cutoffs—high and medium confidence—and integrating pathway and network databases in such a way that the trade-offs of each standalone heuristic are offset by the integrated and iterative analysis approach. SIGNAL is available as a web-based application (https://signal.niaid.nih.gov).