A LASSO penalized regression approach for genome-wide association analyses using related individuals: application to the Genetic Analysis Workshop 19 simulated data
We propose a novel LASSO (least absolute shrinkage and selection operator) penalized regression method used to analyze samples consisting of (potentially) related individuals. Developed in the context of linear mixed models, our method models the relatedness of individuals in the sample through a ra...
| Main Authors: | , , |
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| Format: | Online |
| Language: | English |
| Published: |
BioMed Central
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133525/ |