maNormMain
. It allows the user to choose from a set of six basic location and scale normalization procedures. The function operates on an object of class "marrayRaw"
(or possibly "marrayNorm"
, if normalization is performed in several steps) and returns an object of class "marrayNorm"
.
maNorm(mbatch, norm=c("printTipLoess", "none", "median", "loess",
"twoD", "scalePrintTipMAD"), subset=TRUE, span=0.4, Mloc=TRUE,
Mscale=TRUE, echo=FALSE, ...)
marrayRaw
, containing intensity
data for the batch of arrays to be normalized.
An object of class "marrayNorm"
may also be passed if
normalization is performed in several steps.loess
functionloess
functionloess
functionThis argument can be specified using the first letter of each method.
span
which controls the degree of smoothing in the loess
function.TRUE
, the location normalization values are stored in the slot maMloc
of the object of class "marrayNorm"
returned by the function, if FALSE
, these values are not retained.TRUE
, the scale normalization values are stored in the slot maMscale
of the object of class "marrayNorm"
returned by the function, if FALSE
, these values are not retained.TRUE
, the index of the array currently being
normalized is printed."marrayNorm"
, containing the normalized intensity data.maNormMain
for details and also more general procedures.
Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed (2001). Normalization for cDNA microarray data. In M. L. Bittner, Y. Chen, A. N. Dorsel, and E. R. Dougherty (eds), Microarrays: Optical Technologies and Informatics, Vol. 4266 of Proceedings of SPIE.
Y. H. Yang, S. Dudoit, P. Luu, D. M. Lin, V. Peng, J. Ngai, and T. P. Speed (2002). Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Research, Vol. 30, No. 4.
maNormMain
, maNormScale
.# Examples use swirl dataset, for description type ? swirl
data(swirl)
# Global median normalization for swirl arrays 2 and 3
mnorm<-maNorm(swirl[,2:3], norm="median", echo=TRUE)
# Within-print-tip-group loess location normalization for swirl array 1
mnorm<-maNorm(swirl[,1], norm="p", span=0.45)
Run the code above in your browser using DataLab