I am trying to using loess normalization method to process my proteomics datasets from multiple experiments saved in the format of .csv. The values in the data matrix are intensities of features that were found and determined by proteomics software. There are some missing values in the matrix (less than 2%). The normalize.loess function in the affy package seems to be suitable for this purpose. Please refer to following codes that I tested.
Data<-read.csv("loess_normalization.csv", header=T) normalize.loess(Data)
Unfortunately, I got error message after running normalize.loess.
Error in simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize, : NA/NaN/Inf in foreign function call (arg 1)
What is the meaning of NaN and Inf? Do I need to do log-transformation of my raw intensity data before running? If missing vlaues are problematic for this method, what is the next step that I can follow? Thanks.