Many traits and diseases are thought to be driven by >1 gene (polygenic). Polygenic risk scores (PRS) hence expand on genome-wide association studies by taking multiple genes into account when risk models are built. However, PRS only considers the additive effect of individual genes but not epistatic interactions or the combination of individual and interacting drivers. While evidence of epistatic interactions ais found in small datasets, large datasets have not been processed yet owing to the high computational complexity of the search for epistatic interactions.

中文翻译：

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VariantSpark：基于云的机器学习，用于复杂表型和大规模基因组数据的关联研究。

许多特征和疾病被认为是由 >1 个基因（多基因）驱动的。因此，多基因风险评分 (PRS) 通过在构建风险模型时考虑多个基因来扩展全基因组关联研究。然而，PRS 只考虑单个基因的累加效应，而不考虑上位相互作用或个体和相互作用驱动因素的组合。虽然在小数据集中发现了上位相互作用的证据，但由于搜索上位相互作用的高计算复杂性，尚未处理大数据集。