rmaFitUnit {flagme} | R Documentation |
Using rlm
from MASS, this procedure fits a linear model using all the fragments
rmaFitUnit(u,maxit=5,mzEffect=TRUE,cls=NULL,fitSample=TRUE,fitOrCoef=c("coef","fit"),TRANSFORM=log2)
u |
a metabolite unit (list object with vectors mz and rt for m/z and retention times, respectively and a data element giving the fragmentxsample intensitity matrix) |
maxit |
maximum number of iterations (default: 5) |
mzEffect |
logical, whether to fit m/z effect (default: TRUE ) |
cls |
class variable |
fitSample |
whether to fit individual samples (alternative is fit by group) |
fitOrCoef |
whether to return a vector of coefficients (default: "coef"), or an rlm object ("fit") |
TRANSFORM |
function to transform the raw data to before fitting (default: log2 ) |
Fits a robust linear model.
list
giving elements of fragment
and sample
coefficients (if fitOrCoef="coef"
) or a list
of elements from the fitting process (if fitOrCoef="fit"
)
Mark Robinson
Mark D Robinson (2008). Methods for the analysis of gas chromatography - mass spectrometry data PhD dissertation University of Melbourne.
peaksAlignment
, clusterAlignment
require(gcspikelite) # paths and files gcmsPath<-paste(.find.package("gcspikelite"),"data",sep="/") cdfFiles<-dir(gcmsPath,"CDF",full=TRUE) eluFiles<-dir(gcmsPath,"ELU",full=TRUE) # read data, peak detection results pd<-peaksDataset(cdfFiles[1:2],mz=seq(50,550),rtrange=c(7.5,8.5)) pd<-addAMDISPeaks(pd,eluFiles[1:2]) # pairwise alignment using all scans fullca<-clusterAlignment(pd, usePeaks = FALSE, df = 100) # calculate retention time shifts timedf<-calcTimeDiffs(pd, fullca)