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

• Main Authors: Jennifer Luyapan (Author), Xuemei Ji (Author), Siting Li (Author), Xiangjun Xiao (Author), Dakai Zhu (Author), Eric J. Duell (Author), David C. Christiani (Author), Matthew B. Schabath (Author), Susanne M. Arnold (Author), Shanbeh Zienolddiny (Author), Hans Brunnström (Author), Olle Melander (Author), Mark D. Thornquist (Author), Todd A. MacKenzie (Author), Christopher I. Amos (Author), Jiang Gui (Author)
• Format: Book
• Published: BMC, 2020-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

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...