flagme (version 1.28.0)

normDotProduct: Normalized Dot Product

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

Value

matrix of similarities

Details

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

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]])