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Supervised machine learning and logistic regression identifies novel epistatic risk factors with PTPN22 for rheumatoid arthritis
Investigating genetic interactions (epistasis) has proven difficult despite the recent advances of both laboratory methods and statistical developments. With no ‘best’ statistical approach available, combining several analytical methods may be optimal for detecting epistatic interactions. Using a mu...
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| Hauptverfasser: | , , , , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2010
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3118040/ https://ncbi.nlm.nih.gov/pubmed/20090771 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/gene.2009.110 |
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