Wrapper for processing of LC-MS data files

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Description

Main function of the pipeline for LC-MS data processing. It includes XCMS peak detection, grouping and alignment, CAMERA and feature annotation by comparison to a database of standards. The function also calculates the mass tolerance on the bases of the ion intensity and ion mass.

Usage

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runLC(files, xset, settings, rtrange = NULL, mzrange = NULL, DB = NULL,
      polarity = "positive", errf = NULL, returnXset = FALSE,
      intensity = "into", nSlaves = 0)

Arguments

files

input files, given as a vector of strings containing the complete paths. All formats supported by XCMS can be used.

xset

alternatively, one can present an object of class xsAnnotate, instead of the input files. In that case all of the XCMS and CAMERA tools: peak picking, CAMERA grouping, retention time correction and filling of missing peaks will be considered already done, and only annotation will be performed. This can be useful if one wants to compare different settings for annotation. If both files and xset are given, the former takes precedence.

settings

nested list of settings, to be used at individual steps of the pipeline. See the help of FEMsettings for details.

rtrange

An optional vector to slice the retention time range (in minutes).

mzrange

An optional vector to slice the mass spectrum

DB

database containing the spectra of the pure standards. For the description refer to the LCDBtest help.

polarity

The polarity of the analysis used for CAMERA annotation. Either "positive" or "negative".

errf

A model used to calculate the mass tolerance in ppm for each features on the bases of its mass, retention time and intensity. For further details refer to the help of AnnotateTable.

returnXset

logical: should the XCMS output be returned? If yes, this is a a list of xcmsSet objects, one element for each input file.

intensity

The intensity measure used in the output peaktable. The available intensities are the ones provided by xcms. The default one is the total intensity (integral) of the feature on the detected chromatographic peak.

nSlaves

Number of cores to be used in peak picking.

Details

The mzrange and rtrange parameters are used to subset the mass and retention times considered in the analysis, reducing possible alignment problems at the extremes.
The error function calculates the expected m/z tolerance for feature annotation based on the mz and I values of each feature. To have a more complete description of the process refer to the help of AnnotateTable and the literature reference. An example is provided as well. Note that the use of "lm" is only one of the possible choices, but all kind of functional approximations working with the predict function could be used. If the error function is not provided the mass tolerance will be fixed to the value defined in the settings list.

Value

A list with three elements:

PeakTable

data.frame containing annotation information. Every line is a feature. The first columns are used to give information about these features, annotation, CAMERA, Chemspider IDs, etcetera. The last of these meta-information columns is always the one giving the retention time: "rt". After that, columns correspond to input files, and give measures of intensities for every single one of the features.

Annoation

The complete output of the AnnotateTable function.

Settings

The settings used in the pipeline.

xset

optionally, the xcmsSet/CAMERA object is returned, which can be useful for more detailed inspection of the results.

sessionInfo

The output of sessionInfo() to keep track of the sw version used for the processing

Author(s)

Pietro Franceschi

References

N. Shahaf, P. Franceschi, P. Arapitsas, I. Rogachev, U. Vrhovsek and R. Wehrens: "Constructing a mass measurement error surface to improve automatic annotations in liquid chromatography/mass spectrometry based metabolomics". Rapid Communications in Mass Spectrometry, 27(21), 2425 (2013).

Examples

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data(LCresults)
names(LCresults)

## Not run: 
## load the settings for the analysis
data(FEMsettings)
  
## load the annotation DB
data(LCDBtest)

## load the Synapt Q-TOF error function
data(errf)

results.xset  <- runLC(xset = LCresults$xset, settings = Synapt.RP, 
                       DB = LCDBtest$DB)

## to start directly from the CDF files and include peak picking in the
## pipeline, simply provide the "files" argument rather than the "xset" argument

if (require(metaMSdata)) {
  ## get the path 
  cdfpath <- system.file("extdata", package = "metaMSdata")
  
  ## files 
  files <- list.files(cdfpath, "_RP_", full.names=TRUE)
    
  ## <-------------    Use the Synapt Q-TOF error function     -------------- >
  result.adaptive <- runLC(files, settings = Synapt.RP, 
                           DB = LCDBtest$DB, errf = errf)
  
  ## <--------    Run the analysis with a fixed mass tolerance      --------- >
  result.fixed <- runLC(files, settings = Synapt.RP, 
                        DB = LCDBtest$DB)
}            

## End(Not run)

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