rmaFitUnit: Fits a robust linear model (RLM) for one metabolite
In flagme: Analysis of Metabolomics GC/MS Data

Description Usage Arguments Details Value Author(s) References See Also Examples

Using rlm from MASS, this procedure fits a linear model using all the fragments

1	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)