Pathway Analysis of Rare Variants Using generalized structured component analysis

[Speaker] Park, Taesung:1
[Co-author] Choi, Sungkyoung:1, Lee, Sungyoung:1, Hwang, Heungsun:2
1:Seoul National University (Korea(Republic of Korea)), 2:McGill University (Canada)

Most approaches for rare variants focus mainly on individual gene analysis. However, it has also been recognized that a majority of biological behaviors manifest from a complex interaction of biological pathway. Although several statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually, those methods generally assume that the pathways are independent and do not consider substantial overlapping genes between pathways. In this paper, we propose a novel statistical approach: a robust pathway-based approach using hierarchical components. The proposed method uses generalized structural components and analyzes all pathways from the public databases. To consider the relationship between genes within-pathway, we use both reflective and formative models. Furthermore, our approach uses ridge-regularized method to reduce the effects of the overlapping genes between pathways. Evaluation of the method was performed with the simulation data sets as well as the 1,000 exome sequencing data of Korean population.
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