rmaFitUnit: Fits a robust linear model (RLM) for one metabolite

In rromoli/flagme: Analysis of Metabolomics GC/MS Data

Fits a robust linear model (RLM) for one metabolite

Description

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

Usage

rmaFitUnit(
  u,
  maxit = 5,
  mzEffect = TRUE,
  cls = NULL,
  fitSample = TRUE,
  fitOrCoef = c("coef", "fit"),
  TRANSFORM = log2
)

Arguments

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)

Details

Fits a robust linear model.

Value

list giving elements of fragment and sample coefficients (if fitOrCoef="coef") or a list of elements from the fitting process (if fitOrCoef="fit")

Author(s)

Mark Robinson

References

Mark D Robinson (2008). Methods for the analysis of gas chromatography - mass spectrometry data PhD dissertation University of Melbourne.

See Also

peaksAlignment, clusterAlignment

Examples

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)

rromoli/flagme documentation built on Feb. 10, 2023, 12:59 a.m.