normDotProduct: Normalized Dot Product

In flagme: Analysis of Metabolomics GC/MS Data

Description

This function calculates the similarity of all pairs of peaks from 2 samples, using the spectra similarity

Usage

normDotProduct(x1,x2,t1=NULL,t2=NULL,df=max(ncol(x1),ncol(x2)),D=100000,timedf=NULL,verbose=FALSE)

Arguments

x1	data matrix for sample 1
x2	data matrix for sample 2
t1	vector of retention times for sample 1
t2	vector of retention times for sample 2
df	distance from diagonal to calculate similarity
D	retention time penalty
timedf	matrix of time differences to normalize to. if NULL, 0 is used.
verbose	logical, whether to print out information

Details

Efficiently computes the normalized dot product between every pair of peak vectors and returns a similarity matrix. C code is called.

Value

matrix of similarities

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

dp, peaksAlignment

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])

r<-normDotProduct(pd@peaksdata[[1]],pd@peaksdata[[2]])

flagme documentation built on Nov. 8, 2020, 5:24 p.m.