xcmsSet-class: Class xcmsSet, a class for preprocessing peak data

In benjiec/xcms: LC/MS and GC/MS Data Analysis

Description

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.

Objects from the Class

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", ...).

Slots

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 two values, method - profile generation method, and step - profile m/z step size

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)

Methods

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

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

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

retcor

signature(object = "xcmsSet"): use initial grouping of peaks to do nonlinear loess retention time correction

sampclass<-

signature(object = "xcmsSet"): DEPRECATED. If used, the experimental design will be replaced with a data frame with a single column matching the supplied factor.

sampclass

signature(object = "xcmsSet"): get the interaction of the experimental design factors

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

sampnames<-

signature(object = "xcmsSet"): set rownames in the phenoData slot

sampnames

signature(object = "xcmsSet"): get rownames in the phenoData slot

split

signature("xcmsSet"): divide into a list of objects

Note

No notes yet.

Author(s)

Colin A. Smith, [e-mail]

References

A parallel effort in metabolite profiling data sharing: http://metlin.scripps.edu/

See Also

xcmsSet

benjiec/xcms documentation built on May 12, 2019, 11:57 a.m.