TargetSearch--a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data.
BACKGROUND
Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks.


RESULTS
We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R.


CONCLUSIONS
TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data.
Cuadros-Inostroza
Alvaro
A
Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany. inostroza@mpimp-golm.mpg.de
Caldana
Camila
C
Redestig
Henning
H
Kusano
Miyako
M
Lisec
Jan
J
Peña-Cortés
Hugo
H
Willmitzer
Lothar
L
Hannah
Matthew A
MA
D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D055442:Metabolome; D010363:Pattern Recognition, Automated; D020543:Proteome / Q000032:analysis; D040901:Proteomics / Q000379:methods; D012984:Software; D014584:User-Computer Interface
D020543:Proteome