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Bayesian GWAS with Structured and Non-Local Priors
MOTIVATION: The flexibility of a Bayesian framework is promising for GWAS, but current approaches can benefit from more informative prior models. We introduce a novel Bayesian approach to GWAS, called Structured and Non-Local Priors (SNLPs) GWAS, that improves over existing methods in two important...
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| Pubblicato in: | Bioinformatics |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Oxford University Press
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6956774/ https://ncbi.nlm.nih.gov/pubmed/31651034 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btz518 |
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