Details

Autor(en) / Beteiligte

• Deng, Yamin
• Wu, Shiman
• Fan, Huifang
• Novelli, Giuseppe

Titel

Genome-wide pathway-based quantitative multiple phenotypes analysis

Ist Teil von

• PloS one, 2020-11, Vol.15 (11), p.e0240910-e0240910

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2020

Quelle

MEDLINE

Beschreibungen/Notizen

• For complex diseases, genome-wide pathway association studies have become increasingly promising. Currently, however, pathway-based association analysis mainly focus on a single phenotype, which may insufficient to describe the complex diseases and physiological processes. This work proposes a combination model to evaluate the association between a pathway and multiple phenotypes and to reduce the run time based on asymptotic results. For a single phenotype, we propose a semi-supervised maximum kernel-based U-statistics (mSKU) method to assess the pathway-based association analysis. For multiple phenotypes, we propose the fisher combination function with dependent phenotypes (FC) to transform the p-values between the pathway and each marginal phenotype individually to achieve pathway-based multiple phenotypes analysis. With real data from the Alzheimer Disease Neuroimaging Initiative (ADNI) study and Human Liver Cohort (HLC) study, the FC-mSKU method allows us to specify which pathways are specific to a single phenotype or contribute to common genetic constructions of multiple phenotypes. If we only focus on single-phenotype tests, we may miss some findings for etiology studies. Through extensive simulation studies, the FC-mSKU method demonstrates its advantages compared with its counterparts.