normPred {crmn} | R Documentation |
Predict for normalization
Description
Predict the normalized data using a previously fitted normalization model.
Usage
normPred(normObj, newdata, factors = NULL, lg = TRUE, predfunc = predict, ...)
Arguments
normObj |
the result from |
newdata |
an |
factors |
column names in the pheno data slot describing the biological factors. Or a design matrix. |
lg |
logical indicating that the data should be log transformed |
predfunc |
the function to use to get predicted values from the fitted object (only for crmn) |
... |
passed on to |
Details
Apply fitted normalization parameters to new data to get normalized data. Current can not only handle matrices as input for methods 'RI' and 'one'.
Value
the normalized data
Author(s)
Henning Redestig
See Also
normFit
Examples
data(mix)
nfit <- normFit(mix, "crmn", factor="type", ncomp=3)
normedData <- normPred(nfit, mix, "type")
slplot(pca(t(log2(exprs(normedData)))), scol=as.integer(mix$type))
## same thing
Y <- exprs(mix)
G <- with(pData(mix), model.matrix(~-1+type))
isIS <- fData(mix)$tag == 'IS'
nfit <- normFit(Y, "crmn", factors=G, ncomp=3, standards=isIS)
normedData <- normPred(nfit, Y, G, standards=isIS)
slplot(pca(t(log2(normedData))), scol=as.integer(mix$type))