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http://dx.doi.org/10.5808/GI.2020.18.1.e11

HisCoM-PCA: software for hierarchical structural component analysis for pathway analysis based using principal component analysis  

Jiang, Nan (Interdisciplinary Program in Bioinformatics, Seoul National University)
Lee, Sungyoung (Center for Precision Medicine, Seoul National University Hospital)
Park, Taesung (Interdisciplinary Program in Bioinformatics, Seoul National University)
Abstract
In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.
Keywords
genome-wide association study; hierarchical structural component model; pathway analysis; principal component analysis;
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