| tsLib-class {TargetSearch} | R Documentation |
This is a class representation of a reference library.
Objects can be created by the function ImportLibrary.
Name:"character", the metabolite or analyte names.RI:"numeric", the expected retention time indices (RI) of the metabolites/analytes.medRI:"numeric", the median RI calculated from the samples.RIdev:"matrix", the RI deviation windows, k = 1,2,3. A three column matrixselMass:"list", every component is a numeric vector containing the selective masses. topMass:"list", every component is a numeric vector containing the top masses. libData:"data.frame", additional library information. spectra:"list", the metabolite spectra. Each component is a two column matrix: m/z and intensity. [signature(x = "tsLib"): Selects a subset of metabolites from the library.$namesignature(x = "tsLib"): Access column name of libData slot. libIdsignature(obj = "tsLib"): Returns a vector of indices. lengthsignature(x = "tsLib"): returns the length of the library. i.e., number of metabolites.libDatasignature(obj = "tsLib"): gets the libData slot.libNamesignature(obj = "tsLib"): gets the Name slot. libRIsignature(obj = "tsLib"): gets the RI slot. medRIsignature(obj = "tsLib"): gets the medRI slot. refLibsignature(obj = "tsLib"): Low level method to create a matrix representation of the library.RIdevsignature(obj = "tsLib"): gets the RI deviations. RIdev<-signature(obj = "tsLib"): sets the RI deviations. selMasssignature(obj = "tsLib"): gets the selective masses. showsignature(object = "tsLib"): show method. spectrasignature(obj = "tsLib"): gets the spectra. topMasssignature(obj = "tsLib"): gets the top masses. Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig
showClass("tsLib")
# define some metabolite names
libNames <- c("Metab1", "Metab2", "Metab3")
# the expected retention index
RI <- c(100,200,300)
# selective masses to search for. A list of vectors.
selMasses <- list(c(95,204,361), c(87,116,190), c(158,201,219))
# define the retention time windows to look for the given selective masses.
RIdev <- matrix(rep(c(10,5,2), length(libNames)), ncol = 3, byrow = TRUE)
# Set the mass spectra. A list object of two-column matrices, or set to
# an empty list if the spectra is not available
spectra <- list()
# some extra information about the library
libData <- data.frame(Name = libNames, Lib_RI = RI)
# create a reference library object
refLibrary <- new("tsLib", Name = libNames, RI = RI, medRI = RI, RIdev = RIdev,
selMass = selMasses, topMass = selMasses, spectra = spectra, libData = libData)
# get the metabolite names
libName(refLibrary)
# set new names
libName(refLibrary) <- c("Metab01", "Metab02", "Metab03")
# get the expected retention times
libRI(refLibrary)
# set the retention time index for metabolite 3 to 310 seconds
libRI(refLibrary)[3] <- 310
# change the seleccion and top masses of metabolite 3
selMass(refLibrary)[[3]] <- c(158,201,219,220,323)
topMass(refLibrary)[[3]] <- c(158,201,219,220,323)
# change the retention time deviations
RIdev(refLibrary)[3,] <- c(8,4,1)