Investigating Gene- and Pathway-environment Interaction analysis approaches
Journal de la société française de statistique, Volume 159 (2018) no. 2, pp. 56-83.

Pathway analysis can increase power to detect associations with a gene or a pathway by combining several signals at the single nucleotide polymorphism (SNP)-level into a single test. In this work, we propose to extend two well-known self-contained methods, the Fisher’s method (FM) and the Adaptive Rank Truncated Product (ARTP) method to the analysis of gene-environment (GxE) interaction at the gene and pathway-level. It has been previously suggested that the permutation procedures that are usually used to derive the significance of these tests are not appropriate for the analysis of GxE interaction and should be replaced by a bootstrap approach. We analyse and compare the performance of the extension of FM and ARTP using the permutation and the parametric bootstrap procedure in simulation studies. We illustrate its application by analysing the interaction between night work and circadian gene polymorphisms in the risk of breast cancer in a case-control study. The ARTP method, adapted for both gene- and pathway-environment interactions, gives promising results and has been wrapped to the R package PIGE available on the CRAN.

Les analyses par pathway permettent d’augmenter la puissance statistique en combinant les signaux au niveau des SNPs pour définir des associations au niveau du gène et/ou du pathway. Dans cette étude, nous proposons d’adapter deux méthodes d’analyse par pathway, la méthode de Fisher (FM) et la méthode ARTP (Adaptive Rank Truncated Product), pour l’analyse des interactions gène-environnement (GxE) au niveau du gène et au niveau du pathway. Il a été précédemment suggéré que les procédures de permutations habituellement utilisées pour estimer la significativité de ces tests ne sont pas appropriées pour l’analyse des interactions GxE et devraient être remplacés par une approche Bootstrap. Ainsi, nous analysons et comparons dans une étude de simulation les performances de l’extension des méthodes FM et ARTP en utilisant une procédure de permutation et une méthode de Bootstrap paramétrique. Ces méthodes sont également appliquées aux données de l’étude cas-témoins CECILE sur les cancers du sein dans laquelle nous avons analysé l’interaction entre le travail de nuit et les polymorphismes des gènes circadiens dans le risque de cancer du sein. La méthode ARTP adaptée aux interactions GxE donne des résultats prometteurs. Un package R PIGE a été développé et est mis à disposition sur le CRAN.

Keywords: Gene-environment interactions, Generalized Linear Models, Pathway analysis, Resampling methods
     author = {Broc, Camilo and Evangelou, Marina and Truong, Therese and Guenel, Pascal and Liquet, Benoit},
     title = {Investigating {Gene-} and {Pathway-environment} {Interaction} analysis approaches},
     journal = {Journal de la soci\'et\'e fran\c{c}aise de statistique},
     pages = {56--83},
     publisher = {Soci\'et\'e fran\c{c}aise de statistique},
     volume = {159},
     number = {2},
     year = {2018},
     zbl = {1406.62134},
     language = {en},
     url = {}
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Broc, Camilo; Evangelou, Marina; Truong, Therese; Guenel, Pascal; Liquet, Benoit. Investigating Gene- and Pathway-environment Interaction analysis approaches. Journal de la société française de statistique, Volume 159 (2018) no. 2, pp. 56-83.

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