ruv-package: Detect and Remove Unwanted Variation using Negative Controls
In ruv: Detect and Remove Unwanted Variation using Negative Controls

Description Details Note Author(s) References See Also

Implements the 'RUV' (Remove Unwanted Variation) algorithms. These algorithms attempt to adjust for systematic errors of unknown origin in high-dimensional data. The algorithms were originally developed for use with genomic data, especially microarray data, but may be useful with other types of high-dimensional data as well. These algorithms were proposed in Gagnon-Bartsch and Speed (2012) <doi:10.1093/nar/gkz433>, Gagnon-Bartsch, Jacob and Speed (2013), and Molania, et. al. (2019) <doi:10.1093/nar/gkz433>. The algorithms require the user to specify a set of negative control variables, as described in the references. The algorithms included in this package are 'RUV-2', 'RUV-4', 'RUV-inv', 'RUV-rinv', 'RUV-I', and RUV-III', along with various supporting algorithms.

Package:	ruv
Type:	Package
Version:	0.9.7.1
Date:	2019-08-30
License:	GPL
LazyLoad:	yes
URL:	http://www-personal.umich.edu/~johanngb/ruv/

Additional resources can be found at http://www-personal.umich.edu/~johanngb/ruv/.

Johann Gagnon-Bartsch <johanngb@umich.edu>

Gagnon-Bartsch, J.A. and T.P. Speed (2012). Using control genes to correct for unwanted variation in microarray data. Biostatistics. <doi:10.1093/biostatistics/kxr034>

Gagnon-Bartsch, J.A., L. Jacob, and T.P. Speed (2013). Removing Unwanted Variation from High Dimensional Data with Negative Controls. Technical report. Available at: http://statistics.berkeley.edu/tech-reports/820

Molania, R., J. A. Gagnon-Bartsch, A. Dobrovic, and T. P. Speed (2019). A new normalization for the Nanostring nCounter gene expression assay. Nucleic Acids Research. <doi:10.1093/nar/gkz433>

RUV2, RUV4, RUVinv, RUVrinv, variance_adjust, RUVI, RUVIII