Abstract
Here we introduce the ReliefF machine learning algorithm and some of its extensions for detecting and characterizing epistasis in genetic association studies. We provide a general overview of the method and then highlight some of the modifications that have greatly improved its power for genetic analysis. We end with a few examples of published studies of complex human diseases that have used ReliefF.
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Acknowledgements
This work was supported by National Institutes of Health (NIH) grants AI59694, EY022300, GM103534, GM103506, LM009012, LM010098, and LM011360.
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Moore, J.H. (2015). Epistasis Analysis Using ReliefF. In: Moore, J., Williams, S. (eds) Epistasis. Methods in Molecular Biology, vol 1253. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2155-3_17
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DOI: https://doi.org/10.1007/978-1-4939-2155-3_17
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