tsLib-class: Class for representing a reference library

In acinostroza/TargetSearch: A package for the analysis of GC-MS metabolite profiling data

Class for representing a reference library

Description

This is a class representation of a reference library.

Objects from the Class

Objects can be created by the function ImportLibrary.

Slots

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 matrix

selMass:

"list", every component is a numeric vector containing the selective masses.

topMass:

"list", every component is a numeric vector containing the top masses.

quantMass:

"numeric", the mass used for quantification.

libData:

"data.frame", additional library information.

spectra:

"list", the metabolite spectra. Each component is a two column matrix: m/z and intensity.

Methods

[

signature(x = "tsLib"): Selects a subset of metabolites from the library.

$name

signature(x = "tsLib"): Access column name of libData slot.

libId

signature(obj = "tsLib"): Returns a vector of indices.

length

signature(x = "tsLib"): returns the length of the library. i.e., number of metabolites.

libData

signature(obj = "tsLib"): gets/sets the libData slot.

libName

signature(obj = "tsLib"): gets the Name slot.

libRI

signature(obj = "tsLib"): gets the RI slot.

medRI

signature(obj = "tsLib"): gets the medRI slot.

refLib

signature(obj = "tsLib"): Low level method to create a matrix representation of the library.

RIdev

signature(obj = "tsLib"): gets the RI deviations.

RIdev<-

signature(obj = "tsLib"): sets the RI deviations.

quantMass

signature(obj = "tsLib"): gets the quantification mass.

quantMass<-

signature(obj = "tsLib"): sets the quantification mass.

selMass

signature(obj = "tsLib"): gets the selective masses.

show

signature(object = "tsLib"): show method.

spectra

signature(obj = "tsLib"): gets the spectra.

topMass

signature(obj = "tsLib"): gets the top masses.

c

Combine two or more tsLib objects.

Note

Some care is needed when using the methods quantMass<-, selMass<-, topMass<-. In order to be consistent, the first m/z value of the slot topMass and selMass are equal to quantMass, and the values of selMass are equal to the first couple of values of topMass. In other words, the following constrain is applied.

    quantMass : x[0]
    selMass   : x[0], x[1], ..., x[k]
    topMass   : x[0], x[1], ..., x[k], x[k+1], ..., x[n]

where 1 <= k <= n and x[i] is a m/z value. Thus, using one these methods will change the values of the other slots. In the future, these methods will be deprecated, so it is better to not rely on them.

See the last example on how this can lead to unexpected results.

The c method requires that the combination of all objects have unique identifiers (names), or in other words, the objects cannot share identifiers. Duplicated identifiers are not allowed and an error will be thrown. This method also requires that the column names of the libData slot (see method libData) are the same, because the method calls rbind internally.

Author(s)

Alvaro Cuadros-Inostroza, Matthew Hannah, Henning Redestig

See Also

ImportLibrary

Examples

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
# NULL if the spectra is not available
spectra    <- NULL
# 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 selection 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)

#####################################################################
# objects can be subset and combined with the `[` and `c` operators
lib1 <- refLibrary[1:2]
lib2 <- refLibrary[3]
lib  <- c(lib1, lib2) # this restores the object refLibrary

#####################################################################
# These examples show how changing a quantitaive or selective mass
# could lead to unexpected results.

# show quantMasses
quantMass(refLibrary)

# suppose that we want to change the quant mass of metabolite 1 to 96 due
# to a typo in the library. We could do just
quantMass(refLibrary)[1] <- 96

# however, we still see the mass 95 in the selective and top masses.
selMass(refLibrary)[[1]]
topMass(refLibrary)[[1]]

# to remove the mass 95, set the topMass and selMass explicitly, noting that
# the first masses coincides with 96 (the quantMass)
selMass(refLibrary)[[1]] <- c(96, 204, 361)
topMass(refLibrary)[[1]] <- c(96, 204, 361)

acinostroza/TargetSearch documentation built on June 19, 2024, 12:26 a.m.