IPO-package: Automated Optimization of Untargeted Metabolomics LC-MS Data...
In glibiseller/IPO: Automated Optimization of XCMS Data Processing parameters

IPO-package

R Documentation

Automated Optimization of Untargeted Metabolomics LC-MS Data Processing

Description

IPO provides a framework for parameter optimization for the software package XCMS. It provides optimisation of peak picking parameters by using natural, stable 13C isotopes. Retention time correction is optimized by minimizing the relative retention time differences within features and grouping parameters are optimized by maximizing the number of features showing exactly one peak from each injection of a pooled sample.

Details

An overview of how to use the package, including the most important functions

Author(s)

Gunnar Libiseller

Maintainer: Thomas Riebenbauer <Thomas.Riebenbauer@joanneum.at>

References

Lenth, R. V. (2009). Response-Surface Methods in R , Using rsm. Journal of Statistical Software, 32(7), 1-17. Retrieved from http://www.jstatsoft.org/v32/i07

Smith, C.A. and Want, E.J. and O'Maille, G. and Abagyan,R. and Siuzdak, G.: XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching and identification, Analytical Chemistry, 78:779-787 (2006)

Ralf Tautenhahn, Christoph Boettcher, Steffen Neumann: Highly sensitive feature detection for high resolution LC/MS BMC Bioinformatics, 9:504 (2008)

H. Paul Benton, Elizabeth J. Want and Timothy M. D. Ebbels Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data Bioinformatics, 26:2488 (2010)

Yu, H. (2002). Rmpi: Parallel Statistical Computing in R. R News, 2(2), 10-14. Retrieved from http://cran.r-project.org/doc/Rnews/Rnews_2002-2.pdf

Examples

## Not run: 
mtbls2files <- list.files(file.path(find.package("mtbls2"), "mzML"), 
                          full.names=TRUE)

 
paramsPP <- getDefaultXcmsSetStartingParams()
paramsPP$mzdiff <- -0.001
#paramsPP$ppm <- 25
paramsPP$min_peakwidth <- c(7,14)
paramsPP$max_peakwidth <- c(20,30)
paramsPP$noise <- 10000
resultPP <- optimizeXcmsSet(mtbls2files[1:2], paramsPP, subdir="mtbls2")


paramsRG <- getDefaultRetGroupStartingParams()
paramsRG$gapInit <- 0.2
paramsRG$profStep <- 1
paramsRG$minfrac <- 0.75
resultRG <- optimizeRetGroup(resultPP$best_settings$xset, paramsRG, nSlaves=2)

writeRScript(resultPP$best_settings$parameters, resultRG$best_settings, 
             subdir="mtbls2", 4)

## End(Not run)

glibiseller/IPO documentation built on Dec. 4, 2022, 7:09 a.m.