MS Data Analysis

Description Details Objects from the Class Slots Methods Note Author(s) References See Also

This class transforms a set of peaks from multiple LC/MS or GC/MS samples into a matrix of preprocessed data. It groups the peaks and does nonlinear retention time correction without internal standards. It fills in missing peak values from raw data. Lastly, it generates extracted ion chromatograms for ions of interest.

The phenoData slot (and phenoData parameter in the xcmsSet function) is intended to contain a data.frame describing all experimental factors, i.e. the samples along with their properties. If this data.frame contains a column named “class”, this will be returned by the sampclass method and will thus be used by all methods to determine the sample grouping/class assignment (e.g. to define the colors in various plots or for the group method).

The sampclass<- method adds or replaces the “class” column in the phenoData slot. If a data.frame is submitted to this method, the interaction of its columns will be stored into the “class” column.

Also, similar to other classes in Bioconductor, the $ method can be used to directly access all columns in the phenoData slot (e.g. use xset$name on a xcmsSet object called “xset” to extract the values from a column named “name” in the phenoData slot).

Objects can be created with the xcmsSet constructor which gathers peaks from a set NetCDF files. Objects can also be created by calls of the form new("xcmsSet", ...).

peaks: matrix containing peak data.
filled: A vector with peak indices of peaks which have been added by a fillPeaks method.
groups: Matrix containing statistics about peak groups.
groupidx: List containing indices of peaks in each group.
phenoData: A data.frame containing the experimental design factors.
rt: list containing two lists, raw and corrected, each containing retention times for every scan of every sample.
filepaths: Character vector with absolute path name of each NetCDF file.
profinfo: list containing the values method - profile generation method, and step - profile m/z step size and eventual additional parameters to the profile function.
dataCorrection: logical vector filled if the waters Lock mass correction parameter is used.
polarity: A string ("positive" or "negative" or NULL) describing whether only positive or negative scans have been used reading the raw data.
progressInfo: Progress informations for some xcms functions (for GUI).
progressCallback: Function to be called, when progressInfo changes (for GUI).
mslevel: Numeric representing the MS level on which the peak picking was performed (by default on MS1). This slot should be accessed through its getter method mslevel.
scanrange: Numeric of length 2 specifying the scan range (or NULL for the full range). This slot should be accessed through its getter method scanrange. The scan range provided in this slot represents the scans to which the whole raw data is subsetted.
.processHistory: Internal slot to be used to keep track of performed processing steps. This slot should not be directly accessed by the user.

c: signature("xcmsSet"): combine objects together
filepaths<-: signature(object = "xcmsSet"): set filepaths slot
filepaths: signature(object = "xcmsSet"): get filepaths slot
diffreport: signature(object = "xcmsSet"): create report of differentially regulated ions including EICs
fillPeaks: signature(object = "xcmsSet"): fill in peak data for groups with missing peaks
getEIC: signature(object = "xcmsSet"): get list of EICs for each sample in the set
getXcmsRaw: signature(object = "xcmsSet", sampleidx = 1, profmethod = profMethod(object), profstep = profStep(object), profparam=profinfo(object), mslevel = NULL, scanrange = NULL, rt=c("corrected", "raw"), BPPARAM = bpparam()): read the raw data for one or more files in the xcmsSet and return it. The default parameters will apply all settings used in the original xcmsSet call to generate the xcmsSet object to be applied also to the raw data. Parameter sampleidx allows to specify which raw file(s) should be loaded. Argument BPPARAM allows to setup parallel processing.
groupidx<-: signature(object = "xcmsSet"): set groupidx slot
groupidx: signature(object = "xcmsSet"): get groupidx slot
groupnames: signature(object = "xcmsSet"): get textual names for peak groups
groups<-: signature(object = "xcmsSet"): set groups slot
groups: signature(object = "xcmsSet"): get groups slot
groupval: signature(object = "xcmsSet"): get matrix of values from peak data with a row for each peak group
group: signature(object = "xcmsSet"): find groups of peaks across samples that share similar m/z and retention times
mslevel: Getter method for the mslevel slot.
peaks<-: signature(object = "xcmsSet"): set peaks slot
peaks: signature(object = "xcmsSet"): get peaks slot
plotrt: signature(object = "xcmsSet"): plot retention time deviation profiles
profinfo<-: signature(object = "xcmsSet"): set profinfo slot
profinfo: signature(object = "xcmsSet"): get profinfo slot
profMethod: signature(object = "xcmsSet"): extract the method used to generate the profile matrix.
profStep: signature(object = "xcmsSet"): extract the profile step used for the generation of the profile matrix.
retcor: signature(object = "xcmsSet"): use initial grouping of peaks to do nonlinear loess retention time correction
sampclass<-: signature(object = "xcmsSet"): Replaces the column “class” in the phenoData slot. See details for more information.
sampclass: signature(object = "xcmsSet"): Returns the content of the column “class” from the phenoData slot or, if not present, the interaction of the experimental design factors (i.e. of the phenoData data.frame). See details for more information.
phenoData<-: signature(object = "xcmsSet"): set the phenoData slot
phenoData: signature(object = "xcmsSet"): get the phenoData slot
progressCallback<-: signature(object = "xcmsSet"): set the progressCallback slot
progressCallback: signature(object = "xcmsSet"): get the progressCallback slot
scanrange: Getter method for the scanrange slot. See scanrange slot description above for more details.
sampnames<-: signature(object = "xcmsSet"): set rownames in the phenoData slot
sampnames: signature(object = "xcmsSet"): get rownames in the phenoData slot
split: signature("xcmsSet"): divide the xcmsSet into a list of xcmsSet objects depending on the provided factor. Note that only peak data will be preserved, i.e. eventual peak grouping information will be lost.
object$name, object$name<-value: Access and set name column in phenoData
object[, i]: Conducts subsetting of a xcmsSet instance. Only subsetting on columns, i.e. samples, is supported. Subsetting is performed on all slots, also on groups and groupidx. Parameter i can be an integer vector, a logical vector or a character vector of sample names (matching sampnames).