A Fast Multiple-Kernel Method Based on a Low-Rank Approximation

Description

A computationally efficient and statistically rigorous fast Kernel Machine method for multi-kernel analysis. The approach is based on a low-rank approximation to the nuisance effect kernel matrices. The algorithm is applicable to continuous, dichotomous, and survival traits and is implemented using the existing single-kernel analysis software 'SKAT' or 'coxKM'.

Details

Author(s)

Shannon T. Holloway, Rachel Marceau, Wenbin Lu, Michele M. Sale, Bradford B. Worrall, Stephen R. Williams, Fang-Chi Hsu, and Jung-Ying Tzeng

Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>

References

Marceau, R., Lu, W., Holloway, S. T., Sale, M. M., Worrall, B. B., Williams, S. R., Hsu, F-C., and Tzeng, J-Y. (2015). A Fast Multiple-Kernel Method with Applications to Detect Gene-Environment Interaction. Genetic Epidemiology, 39, 456-468.

Results