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A software tool for the efficient and automatic analysis of GC/MS-based metabolomics data. Starting with raw MS data, MetaboliteDetector detects and subsequently identifies potential metabolites. Moreover, a comparative analysis of a large number of chromatograms can be performed in either a targeted or nontargeted approach. It automatically determines appropriate quantification ions and performs an integration of single ion peaks. The analysis results can directly be visualized with a principal component analysis. Since the manual input is limited to absolutely necessary parameters, the program is also usable for the analysis of high-throughput data. However, the intuitive graphical user interface of MetaboliteDetector additionally allows for a detailed examination of a single GC/MS chromatogram including single ion chromatograms, recorded mass spectra, and identified metabolite spectra in combination with the corresponding reference spectra obtained from a reference library. MetaboliteDetector is able to import GC/MS data in NetCDF and FastFlight format.


Represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R).


An open source tool which is a flexible and accurate method for pre-processing very large numbers of GC-MS samples within hours. A novel strategy was developed to iteratively correct and update retention time indices for searching and identifying metabolites. TargetSearch includes a graphical user interface to allow easy use by those unfamiliar with R. It allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software.

MET-IDEA / Metabolomics Ion-based Data Extraction Algorithm

A current and significant limitation to metabolomics is the large-scale, high-throughput conversion of raw chromatographically coupled mass spectrometry datasets into organized data matrices necessary for further statistical processing and data visualization. MET-IDEA is a data extraction tool which surmounts this void. It is compatible with a diversity of chromatographically coupled mass spectrometry systems, generates an output similar to traditional quantification methods, utilizes the sensitivity and selectivity associated with selected ion quantification, and greatly reduces the time and effort necessary to obtain large-scale organized datasets by several orders of magnitude.


Aims to compare and evaluate various publicly available open source label-free data processing workflows. msCompare is a modular framework that allows the arbitrary combination of different feature detection/quantification and alignment/matching algorithms in conjunction with a scoring method to evaluate their overall performance. msCompare was used to assess the performance of workflows built from modules of publicly available data processing packages such as SuperHirn, OpenMS, and MZmine and in-house developed modules. It was found that the quality of results varied greatly among workflows, and interestingly, heterogeneous combinations of algorithms often performed better than the homogenous workflows. This scoring method showed that the union of feature matrices of different workflows outperformed the original homogenous workflows in some cases. msCompare is available as a standalone command line program or can be used through a Graphical User Interface (GUI) into the Galaxy framework.


Comprises a library of functions for processing of instrument gas chromatography–mass spectrometry (GC-MS) data. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. It implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments.