r-sva 3.36.0 Surrogate variable analysis
This package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. It also contains functions for identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data like gene expression/RNA sequencing/methylation/brain imaging data that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise.
- Website: https://bioconductor.org/packages/sva
- License: Artistic License 2.0
- Package source: bioinformatics.scm
- Patches: None
- Builds: x86_64-linux, i686-linux