Profile {TargetSearch} | R Documentation |
This function makes a profile from the masses that correlate for each metabolite.
Profile(samples, Lib, peakData, r_thres = 0.95, method = "dayNorm", minPairObs = 5)
samples |
A tsSample object created by ImportSamples function. |
Lib |
A tsLib object created by ImportLibrary function with corrected RI values.
See medianRILib . |
peakData |
A tsMSdata object. See peakFind . |
r_thres |
A correlation threshold. |
method |
Normalisation method. Options are "dayNorm" , a day based median
normalisation, "medianNorm" , normalisation using the median of all the intensities
of a given mass, and "none" , no normalisation at all. |
minPairObs |
Minimum number of pair observations. Correlations between two variables are computed using all complete pairs of observations in those variables. If the number of observations is too small, you may get high correlations values just by chance, so this parameters is used to avoid that. |
A tsProfile
object. The slots are:
Info |
A data frame with a profile of all masses that correlate. |
Intensity |
A matrix with the averaged intensities of the correlating masses. |
RI |
A matrix with the averaged RI of the correlating masses. |
Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig
ImportSamples
, ImportLibrary
, medianRILib
,
peakFind
, tsProfile
require(TargetSearchData) data(TargetSearchData) # get RI file path RI.path <- file.path(.find.package("TargetSearchData"), "gc-ms-data") # update RI file path RIpath(sampleDescription) <- RI.path # update median RI refLibrary <- medianRILib(sampleDescription, refLibrary) # get the sample RI corRI <- sampleRI(sampleDescription, refLibrary, r_thres = 0.95) # obtain the peak Intensities of all the masses in the library peakData <- peakFind(sampleDescription, refLibrary, corRI) # make a profile of the metabolite data metabProfile <- Profile(sampleDescription, refLibrary, peakData, r_thres = 0.95) # same as above, but with different thresholds. metabProfile <- Profile(sampleDescription, refLibrary, peakData, r_thres = 0.9, minPairObs = 5)