Not Just a Sum? Identifying Different Types of Interplay between Constituents in Combined Interventions

MotivationExperiments in which the effect of combined manipulations is compared with the effects of their pure constituents have received a great deal of attention. Examples include the study of combination therapies and the comparison of double and single knockout model organisms. Often the effect of the combined manipulation is not a mere addition of the effects of its constituents, with quite different forms of interplay between the constituents being possible. Yet, a well-formalized taxonomy of possible forms of interplay is lacking, let alone a statistical methodology to test for their presence in empirical data.ResultsStarting from a taxonomy of a broad range of forms of interplay between constituents of a combined manipulation, we propose a sound statistical hypothesis testing framework to test for the presence of each particular form of interplay. We illustrate the framework with analyses of public gene expression data on the combined treatment of dendritic cells with curdlan and GM-CSF and show that these lead to valuable insights into the mode of action of the constituent treatments and their combination.Availability and ImplementationR code implementing the statistical testing procedure for microarray gene expression data is available as supplementary material. The data are available from the Gene Expression Omnibus with accession number GSE32986.研究背景：将联合干预措施的效应与其单一组分的效应进行对比的实验已受到广泛关注，此类研究的实例涵盖联合疗法相关研究，以及双基因敲除（double knockout）与单基因敲除（single knockout）模式生物的效应对比。通常，联合干预的效应并非其各组分效应的简单叠加，组分间可存在多种不同形式的相互作用。然而，目前仍缺乏一套系统完善的各类可能相互作用形式的形式化分类体系，更遑论用于在实验数据中检验此类相互作用是否存在的统计方法。 研究结果：本研究基于联合干预各组分间各类相互作用形式的分类体系，提出了一套严谨的统计假设检验框架，用于检验每种特定形式的相互作用是否存在。我们通过分析树突状细胞经凝胶多糖（curdlan）与粒细胞-巨噬细胞集落刺激因子（GM-CSF）联合处理的公开基因表达数据，对该框架进行了实例演示，并证实该分析可助力我们深入理解各单一处理措施及其联合使用的作用模式。 可用性与实现：用于微阵列基因表达数据统计检验流程的R代码已作为补充材料公开。相关数据集可从基因表达综合数据库（Gene Expression Omnibus）获取，登录号为GSE32986。