Mapping genetic interactions (GIs) can reveal important insights into cellular function and has potential translational applications. There has been great progress in developing high-throughput experimental systems for measuring GIs (e.g. with double knockouts) as well as in defining computational methods for inferring (imputing) unknown interactions. However, existing computational methods for imputation have largely been developed for and applied in baker’s yeast, even as experimental systems have begun to allow measurements in other contexts. Importantly, existing methods face a number of limitations in requiring specific side information and with respect to computational cost. Further, few have addressed how GIs can be imputed when data are scarce.

中文翻译：

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重新加载矩阵（分解）：利用种间和边际信息估算遗传相互作用的灵活方法

映射遗传相互作用（GI）可以揭示细胞功能的重要见解，并具有潜在的翻译应用。在开发用于测量GI（例如双敲除）的高通量实验系统以及定义用于推断（估算）未知相互作用的计算方法方面，已经取得了很大的进步。然而，即使实验系统已经开始允许在其他情况下进行测量，现有的估算方法也已经为面包酵母开发并应用于面包酵母中。重要的是，现有方法在要求特定的辅助信息以及计算成本方面面临许多限制。此外，很少有人讨论在数据匮乏时如何推算地理标志。