Extensions of sparse canonical correlation analysis with applications to genomic data.

@article{Witten2009ExtensionsOS,
  title={Extensions of sparse canonical correlation analysis with applications to genomic data.},
  author={Daniela M. Witten and Robert Tibshirani},
  journal={Statistical applications in genetics and molecular biology},
  year={2009},
  volume={8},
  pages={
          Article28
        }
}
In recent work, several authors have introduced methods for sparse canonical correlation analysis (sparse CCA). Suppose that two sets of measurements are available on the same set of observations. Sparse CCA is a method for identifying sparse linear combinations of the two sets of variables that are highly correlated with each other. It has been shown to be useful in the analysis of high-dimensional genomic data, when two sets of assays are available on the same set of samples. In this paper… CONTINUE READING

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