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A scalable and portable framework for massively parallel variable selection in genetic association studies
Summary: The deluge of data emerging from high-throughput sequencing technologies poses large analytical challenges when testing for association to disease. We introduce a scalable framework for variable selection, implemented in C++ and OpenCL, that fits regularized regression across multiple Graph...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2012
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3289918/ https://www.ncbi.nlm.nih.gov/pubmed/22238272 http://dx.doi.org/10.1093/bioinformatics/bts015 |