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

Documentation:

Reference manual:

SmartSVA.pdf

Downloads:

Package source:	SmartSVA_0.1.3.tar.gz
Windows binaries:	r-devel: SmartSVA_0.1.3.zip, r-release: SmartSVA_0.1.3.zip, r-oldrel: SmartSVA_0.1.3.zip
macOS binaries:	r-release (arm64): SmartSVA_0.1.3.tgz, r-oldrel (arm64): SmartSVA_0.1.3.tgz, r-release (x86_64): SmartSVA_0.1.3.tgz, r-oldrel (x86_64): SmartSVA_0.1.3.tgz
Old sources:	SmartSVA archive

Reverse dependencies:

Reverse imports:

MEAL, omicRexposome

Linking:

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