SmartSVA: Fast and Robust Surrogate Variable Analysis
Introduces a fast and efficient Surrogate Variable Analysis algorithm that captures variation of unknown sources (batch effects) for high-dimensional data sets. The algorithm is built on the 'irwsva.build' function of the 'sva' package and proposes a revision on it that achieves an order of magnitude faster running time while trading no accuracy loss in return.
| Version: |
0.1.3 |
| Depends: |
R (≥ 3.1.0), sva, isva, RSpectra |
| Imports: |
Rcpp, stats, utils |
| LinkingTo: |
Rcpp, RcppEigen |
| Published: |
2017-05-28 |
| Author: |
Jun Chen, Ehsan Behnam |
| Maintainer: |
Jun Chen <Chen.Jun2 at mayo.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
SmartSVA results |
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