학술논문
Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods
Document Type
article
Author
Source
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Subject
Language
English
ISSN
2045-2322
Abstract
Abstract Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and plasma lipidome (phenotype) in order to identify the genetic architecture of plasma lipidome profiled from 1,426 Finnish individuals aged 30–45 years. PGMRA involves biclustering genotype and lipidome data independently followed by their inter-domain integration based on hypergeometric tests of the number of shared individuals. Pathway enrichment analysis was performed on the SNP sets to identify their associated biological processes. We identified 93 statistically significant (hypergeometric p-value