Philip J Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S Chitre, Oksana Polesskaya, Celine L St Pierre, Jianjun Gao, Connor D Martin, Hao Chen, Angel G Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli, Christopher P King, Abraham A Palmer, Ruowang Li, Jason H Moore
BACKGROUND: Quantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets...
April 10, 2023: BioData Mining