ruv_varianceplot

A scatter plot of (squared) coefficient estimates against variance estimates.

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.

Johann Gagnon-Bartsch

Detect and Remove Unwanted Variation using Negative Controls

ruv_varianceplot function

<dl> <dt>fit</dt>
<dd>The results of a call to <code>ruv_summary</code>.</dd> <dt>X.col</dt>
<dd>Which column of the X matrix to make the plot for. Can be either an integer or a character string.</dd> <dt>power</dt>
<dd>Power transformation of the x and y axes. Default is fourth root.</dd></dl>

Arguments

Author

RUV Variance Plot — ruv_varianceplot

<dl>

 <dt>fit</dt>
<dd>The results of a call to <code>ruv_summary</code>.</dd>

 <dt>X.col</dt>
<dd>Which column of the X matrix to make the plot for. Can be either an integer or a character string.</dd>

 <dt>power</dt>
<dd>Power transformation of the x and y axes. Default is fourth root.</dd>

</dl>

ruv_varianceplot: RUV Variance Plot

Description

Usage

Value

Arguments

Author

Details