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Robust gene-environment interaction analysis using penalized trimmed regression
In biomedical and epidemiological studies, gene-environment (G-E) interactions have been shown to importantly contribute to the etiology and progression of many complex diseases. Most existing approaches for identifying G-E interactions are limited by the lack of robustness against outliers/contamin...
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| Publicado no: | J Stat Comput Simul |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6358205/ https://ncbi.nlm.nih.gov/pubmed/30718937 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/00949655.2018.1523411 |
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