normexpsignal: Expected Signal Given Observed Foreground Under Normal+Exp...
In hdeberg/limma: Linear Models for Microarray Data

Description Usage Arguments Details Value Author(s) References See Also Examples

Adjust foreground intensities for observed background using Normal+Exp Model. This function is called by backgroundCorrect and is not normally called directly by the user.

1	normexp.signal(par, x)

`par`	numeric vector containing the parameters of the Normal+Exp distribution, see `normexp.fit` for details.
`x`	numeric vector of (background corrected) intensities

In general the vector normmean is computed conditional on background at each spot.

Numeric vector containing adjusted intensities.

Gordon Smyth

Ritchie, M. E., Silver, J., Oshlack, A., Silver, J., Holmes, M., Diyagama, D., Holloway, A., and Smyth, G. K. (2007). A comparison of background correction methods for two-colour microarrays. Bioinformatics 23, 2700-2707. http://bioinformatics.oxfordjournals.org/content/23/20/2700

Silver, JD, Ritchie, ME, and Smyth, GK (2009). Microarray background correction: maximum likelihood estimation for the normal-exponential convolution. Biostatistics 10, 352-363. http://biostatistics.oxfordjournals.org/content/10/2/352

normexp.fit

An overview of background correction functions is given in 04.Background.