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Pathway-based approach using hierarchical components of collapsed rare variants.


ABSTRACT:

Motivation

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.

Results

Through simulation studies, the proposed method was shown to have higher statistical power than the existing pathway-based methods. In addition, our method was applied to the large-scale whole-exome sequencing data with levels of a liver enzyme using two well-known pathway databases Biocarta and KEGG. This application demonstrated that our method not only identified associated pathways but also successfully detected biologically plausible pathways for a phenotype of interest. These findings were successfully replicated by an independent large-scale exome chip study.

Availability and implementation

An implementation of PHARAOH is available at http://statgen.snu.ac.kr/software/pharaoh/

Contact

tspark@stats.snu.ac.kr

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Lee S 

PROVIDER: S-EPMC5013912 | biostudies-literature |

REPOSITORIES: biostudies-literature

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