Gradient Boosting as a SNP Filter: an Evaluation Using Simulated and Hair Morphology Data

@inproceedings{Lubke2013GradientBA,
  title={Gradient Boosting as a SNP Filter: an Evaluation Using Simulated and Hair Morphology Data},
  author={G H Lubke and Charles Laurin and Raymond Walters and Nicholas Eriksson and Pirro G Hysi and Tim D. Spector and G Montgomery and N. Mart{\'i}n and S E Medland and D Boomsma},
  booktitle={Journal of data mining in genomics & proteomics},
  year={2013}
}
Typically, genome-wide association studies consist of regressing the phenotype on each SNP separately using an additive genetic model. Although statistical models for recessive, dominant, SNP-SNP, or SNP-environment interactions exist, the testing burden makes an evaluation of all possible effects impractical for genome-wide data. We advocate a two-step approach where the first step consists of a filter that is sensitive to different types of SNP main and interactions effects. The aim is to… CONTINUE READING
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Gradient Boosting as a SNP Filter : an Evaluation Using Simulated and Hair Morphology Data

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