SmartSVA introduces an improved Surrogate Variable Analysis algorithm that automatically captures salient features from data in the presence of confounding factors. SmartSVA proposes a revision on the popular SVA algorithm and on average achieves 10 times faster running time while trading no accuracy loss in return.
Smart SVA requires "sva" and "isva" packages. Start R and install these packages as follows:
Installing "sva" (try http:// if https:// URLs are not supported)
source("https://bioconductor.org/biocLite.R")
biocLite("sva")
Installing "isva"
install.packages("isva")
You may need to install / update other required R packages for "sva" and "isva" to function properly.
You may obtain the lastest revision of SmartSVA by cloning this repository:
> git clone --recursive https://github.com/ehsanbehnam/SmartSVA/For a simple usage example, refer to the sample example given with the source code.
Jun Chen Chen.Jun2@mayo.edu
Ehsan Behnam behnamgh@usc.edu
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.