pre_mQTL {mQTL.NMR} | R Documentation |
Makes use of SRV to preprocess metabolomic data for dimensionality reduction by statistical recoupling of variables
pre_mQTL(infile, outfile, RedMet="SRV", met="sum", corrT = 0.9, BinWidth=0.01)
infile |
metabolomic datafile in csvs format |
outfile |
reduced metabolomic datafile in csvs format |
met |
a charcater specifying the used statistical summary |
RedMet |
a charcater indicating the used dimensionality reduction method: Redmet="SRV" for statistical recoupling of variables and Redmet="bin" to apply the bining approach |
corrT |
a numerical parameter indicating correlation threshold |
BinWidth |
a numerical parameter indicating the bining width |
mQTL-NMR package implements two dimensionality reduction methods. The first one concerns the SRV algorithm which forms clusters of variables using a measure of a local spectral dependency. The second one concerns the classical bining method which divides the spectra into evenly spaced windows (bins) whose width commonly ranges between 0.001 and 0.05 ppm.
variables are associated into a series of clusters (or bins). This function provides in output the paramaters of the clusters (min and max borders, mean,...)
Lyamine Hedjazi
- Blaise,B. et al (2009) Statistical recoupling prior to significance testing in nuclear magnetic resonance based metabonomics, Anal. Chem., 81(15), 6242-6251. - S praul, M.; Neidig, P.; Klauck, U.; Kessler, P.; Holmes, E.; Nicholson, J. K.; Sweatman, B.C.; Salman, S.R.; Farrant, R.D.; Rahr, E.; et al. J.Pharm. Biomed. Anal. 1994, 12, 1215-1225.
# Download data files load_datafiles() # Format data format_mQTL(phenofile,genofile,physiodat,cleandat,cleangen) # Constant Sum normlisation nmeth<-'CS' normalise_mQTL(cleandat,CSnorm,nmeth) # Alignment align_mQTL(CSnorm,aligdat) # Dimensionality reduction met="rectangle" # choose the statistical summarizing measure ("max","sum","trapez",...) RedMet="SRV" # reduction method ("SRV" or "bin") pre_mQTL(aligdat, reducedF, RedMet="SRV",met, corrT=0.9)