calcCaS-methods: EIC correlation grouping of LC/ESI-MS data

In sneumann/CAMERA: Collection of annotation related methods for mass spectrometry data

EIC correlation grouping of LC/ESI-MS data

Description

Calculate the correlation across samples. Filtering correlation with specific parameters and returns a correlation matrix.

Usage

  calcCaS(object,corval=0.75, pval=0.05, intval="into")

Arguments

object	The xsAnnotate object
corval	Correlation threshold for positive hits
pval	P-Value threshold for significance level of correlation
intval	Selection of the intensity values that should be used in the correlation analysis. Can be into, maxo or intb.

Details

Calculate pearson correlation between the peak intensites over all samples. Afterwards use cor.test for returning only significant correlation. Returns only those correlation, which are above both threshold. Set corval and pval to 0 to get the unfiltered correlation matrix. If the object is pregrouped with groupFWHM, then the correlation is only calculated between peaks within a pseudospectrum. Otherwise between all peaks.

Value

A matrix with 4 columns:

x	peak index according to peaktable
y	peak index according to peaktable
cor	correlation value between peak x and peak y
ps	pseudospektrum index for both peaks

Author(s)

Carsten Kuhl <[e-mail]>

See Also

calcCiS groupCorr xsAnnotate-class

Examples

 library(CAMERA)
 #Multiple sample 
 library(faahKO)
 xs.grp       <- group(faahko)
 #create xsAnnotate object 
 xsa          <- xsAnnotate(xs.grp)
 #generate pseudospectra
 xsa.group    <- groupFWHM(xsa)
 #calculate correlation
 correlationMatrix <- calcCaS(xsa.group)

sneumann/CAMERA documentation built on April 5, 2024, 2:33 a.m.