Perform Loess normalization
normalize_loess(omicsData, method = "fast", span = 0.4)an object of the class 'pepData', 'proData', 'metabData',
'lipidData', or 'nmrData', created by as.pepData,
as.proData, as.metabData,
as.lipidData, or as.nmrData, respectively. The
function group_designation must have been run on omicsData to
use several of the subset functions (i.e. rip and ppp_rip).
character string specifying which variant of the cyclic loess method to use. Options are "fast" (default), "affy", or "pairs"
span of loess smoothing window, between 0 and 1.
The normalized data is returned in an object of the appropriate S3 class (e.g. pepData), on the same scale as omicsData (e.g. if omicsData contains log2 transformed data, the normalization will be performed on the non-log2 scale and then re-scaled after normalization to be returned on the log2 scale).
A wrapper for the normalizeCyclicLoess function from the limma package.
Bolstad, B. M., Irizarry R. A., Astrand, M., and Speed, T. P. (2003). A comparison of normalization methods for high density oligonucleotide array data based on bias and variance. Bioinformatics 19, 185-193.
Ballman, KV Grill, DE, Oberg, AL and Therneau, TM (2004). Faster cyclic loess: normalizing RNA arrays via linear models. Bioinformatics 20, 2778-2786.
normalizeCyclicLoess in the limma package
library(pmartRdata)
mypep <- edata_transform(pep_object, "log2")
result <- normalize_loess(mypep)