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Pathway-based approach using hierarchical components of collapsed rare variants
Author(s) -
Sungyoung Lee,
Sungkyoung Choi,
Young Jin Kim,
Bong-Jo Kim,
Heungsun Hwang,
Taesung Park
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw425
Subject(s) - kegg , computer science , computational biology , software , exome , data mining , biology , phenotype , gene , exome sequencing , genetics , transcriptome , gene expression , programming language
To address 'missing heritability' issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem.

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