ruv_scree

The data matrix. Rows are observations and columns are features (e.g. genes). If not specified, Y.svd must be specified instead (which is faster).

Any variables to regress out of Y as a preprocessing step. May simply be 1 (the default) for an intercept term, i.e. the columns of Y are mean centered. May also be <code>NULL</code>.

The SVD of Y, as returned by the svd function.

Y.svd

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.

ruv_scree: RUV Scree Plot

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