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Genetic Variants Detection Based on Weighted Sparse Group Lasso
2020
Frontiers in Genetics
Identification of genetic variants associated with complex traits is a critical step for improving plant resistance and breeding. Although the majority of existing methods for variants detection have good predictive performance in the average case, they can not precisely identify the variants present in a small number of target genes. In this paper, we propose a weighted sparse group lasso (WSGL) method to select both common and low-frequency variants in groups. Under the biologically realistic
doi:10.3389/fgene.2020.00155
pmid:32194631
pmcid:PMC7063084
fatcat:lvt6ezzcoja6rptavxuwdwxrji