Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional genomic data. The algorithm is based on the popular 'SVA' package and proposes a revision on it that achieves more than 10 times faster running time while trading no accuracy loss in return.
|Author||Jun Chen <Chen.Jun2@mayo.edu>, Ehsan Behnam <email@example.com>|
|Date of publication||2016-11-24 00:05:49|
|Maintainer||Jun Chen <Chen.Jun2@mayo.edu>|
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