A new efficient method to detect genetic interactions for lung cancer GWAS

A new efficient method to detect genetic interactions for lung cancer GWAS

Abstract Background Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenge...

Full description

Bibliographic Details
Main Authors: Jennifer Luyapan, Xuemei Ji, Siting Li, Xiangjun Xiao, Dakai Zhu, Eric J. Duell, David C. Christiani, Matthew B. Schabath, Susanne M. Arnold, Shanbeh Zienolddiny, Hans Brunnström, Olle Melander, Mark D. Thornquist, Todd A. MacKenzie, Christopher I. Amos, Jiang Gui
Format: Article
Language:English
Published: BMC 2020-10-01
Series:BMC Medical Genomics
Subjects:
Genetic interactions
Machine learning
Genome-wide association study
Lung cancer
Online Access:http://link.springer.com/article/10.1186/s12920-020-00807-9

Internet

http://link.springer.com/article/10.1186/s12920-020-00807-9

Similar Items