publication . Article . 2009

Combining least absolute shrinkage and selection operator (LASSO) and principal-components analysis for detection of gene-gene interactions in genome-wide association studies

D'Angelo Gina M; Rao DC; Gu C Charles;
Open Access English
  • Published: 01 Dec 2009 Journal: BMC Proceedings, volume 3, issue Suppl 7, page S62 (issn: 1753-6561, Copyright policy)
  • Publisher: Springer Nature
<p>Abstract</p> <p>Variable selection in genome-wide association studies can be a daunting task and statistically challenging because there are more variables than subjects. We propose an approach that uses principal-component analysis (PCA) and least absolute shrinkage and selection operator (LASSO) to identify gene-gene interaction in genome-wide association studies. A PCA was used to first reduce the dimension of the single-nucleotide polymorphisms (SNPs) within each gene. The interaction of the gene PCA scores were placed into LASSO to determine whether any gene-gene signals exist. We have extended the PCA-LASSO approach using the bootstrap to estimate the s...
arXiv: Quantitative Biology::GenomicsQuantitative Biology::Molecular Networks
free text keywords: General Biochemistry, Genetics and Molecular Biology, General Medicine, Lasso (statistics), Logistic regression, Feature selection, Genetic association, Data mining, computer.software_genre, computer, Medicine, business.industry, business, Generalized linear model, Bootstrapping (electronics), Genome-wide association study, Bioinformatics, Principal component analysis, Proceedings, R, Science, Q
Related Organizations
Funded by
NIH| Genetic Analysis of Common Diseases: An Evaluation
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01GM031575-22
NIH| Washington University Institute of Clinical and Translational Sciences (UL1)
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3UL1RR024992-03S4

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