backgroundCorrect {limma} | R Documentation |
Background correct microarray expression intensities.
backgroundCorrect(RG, method="subtract", offset=0, printer=RG$printer, verbose=TRUE)
RG |
an RGList object or a unclassed list containing the same components as an RGList |
method |
character string specifying correction method. Possible values are "none" , "subtract" , "half" , "minimum" , "movingmin" , "edwards" , "normexp" or "rma" . |
offset |
numeric value to add to intensities |
printer |
a list containing printer layout information, see PrintLayout-class |
verbose |
logical, should progress be reported to standard output |
If method="none"
then the corrected intensities are equal to the foreground intensities, i.e., the background intensities are treated as zero.
If method="subtract"
then this function simply subtracts the background intensities from the foreground intensities which is the usual background correction method.
If method="movingmin"
then the background estimates are replaced with the minimums of the backgrounds of the spot and its eight neighbors, i.e., the background is replaced by a moving minimum of 3x3 grids of spots.
The remaining methods are all designed to produce positive corrected intensities.
If method="half"
then any intensity which is less than 0.5 after background subtraction is reset to be equal to 0.5.
If method="minimum"
then any intensity which is zero or negative after background subtraction is set equal to half the minimum of the positive corrected intensities for that array.
If method="edwards"
a log-linear interpolation method is used to adjust lower intensities as in Edwards (2003).
If method="normexp"
a convolution of normal and exponential distributions is fitted to the foreground intensities using the background intensities as a covariate, and the expected signal given the observed foreground becomes the corrected intensity.
This results in a smooth monotonic transformation of the background subtracted intensities such that all the corrected intensities are positive.
See Smyth (2005) and normexp.fit
for more details.
The offset
can be used to add a constant to the intensities before log-transforming, so that the log-ratios are shrunk towards zero at the lower intensities.
This may eliminate or reverse the usual 'fanning' of log-ratios at low intensities associated with local background subtraction.
Background correction (background subtraction) is also performed by the normalizeWithinArrays
method for RGList
objects, so it is not necessary to call backgroundCorrect
directly unless one wants to use a method other than simple subtraction.
Calling backgroundCorrect
before normalizeWithinArrays
will over-ride the default background correction.
An RGList
object in which components R
and G
are background corrected
and components Rb
and Gb
are removed.
Gordon Smyth
Edwards, D. E. (2003). Non-linear normalization and background correction in one-channel cDNA microarray studies Bioinformatics 19, 825-833.
Smyth, G. K. (2005). Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer, New York, pages 397-420.
Yang, Y. H., Buckley, M. J., Dudoit, S., and Speed, T. P. (2002). Comparison of methods for image analysis on cDNA microarray data. Journal of Computational and Graphical Statistics 11, 108-136.
Yang, Y. H., Buckley, M. J., and Speed, T. P. (2001). Analysis of microarray images. Briefings in Bioinformatics 2, 341-349.
An overview of background correction functions is given in 04.Background
.
RG <- new("RGList", list(R=c(1,2,3,4),G=c(1,2,3,4),Rb=c(2,2,2,2),Gb=c(2,2,2,2))) backgroundCorrect(RG) backgroundCorrect(RG, method="half") backgroundCorrect(RG, method="minimum") backgroundCorrect(RG, offset=5)