TY - GEN A1 - Lisec, Jan T1 - ABID N2 - In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context. KW - Software KW - Antibody KW - MALDI PY - 2022 UR - https://github.com/BAMresearch/ABID PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-56192 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - CorMID - Correct Mass Isotopologue Distribution Vectors N2 - The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN. KW - Mass Spectrometry KW - Software KW - R package KW - Mass Isotopomer Distribution KW - Flux Analysis PY - 2022 UR - https://github.com/cran/CorMID/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-56442 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - IsoCor N2 - Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis. KW - Shiny-App KW - ICP-MS KW - Software PY - 2022 UR - https://github.com/cran/IsoCor/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-56307 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - CorrectOverloadedPeaks (R package to correct APCI-HR-MS peak data) N2 - Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays. KW - Software KW - Metabolomics KW - R package KW - Data processing PY - 2019 UR - https://github.com/cran/CorrectOverloadedPeaks/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57853 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - MetabolomicsBasics (R package to process and analyze metabolomics datasets) N2 - Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification. KW - Software KW - Mass Spectrometry KW - R package KW - Data processing PY - 2018 UR - https://github.com/cran/MetabolomicsBasics/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57854 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Lisec, Jan T1 - InterpretMSSpectrum (R package to annotate mass spectra) N2 - Gas chromatography using atmospheric pressure chemical ionization coupled to mass spectrometry (GC/APCI-MS) is an emerging metabolomics platform, providing much-enhanced capabilities for structural mass spectrometry as compared to traditional electron ionization (EI)-based techniques. To exploit the potential of GC/APCI-MS for more comprehensive metabolite annotation, a major bottleneck in metabolomics, we here present the novel R-based tool InterpretMSSpectrum assisting in the common task of annotating and evaluating in-source mass spectra as obtained from typical full-scan experiments. After passing a list of mass-intensity pairs, InterpretMSSpectrum locates the molecular ion (M0), fragment, and adduct peaks, calculates their most likely sum formula combination, and graphically summarizes results as an annotated mass spectrum. Using (modifiable) filter rules for the commonly used methoximated-trimethylsilylated (MeOx-TMS) derivatives, covering elemental composition, typical substructures, neutral losses, and adducts, InterpretMSSpectrum significantly reduces the number of sum formula candidates, minimizing manual effort for postprocessing candidate lists. We demonstrate the utility of InterpretMSSpectrum for 86 in-source spectra of derivatized standard compounds, in which rank-1 sum formula assignments were achieved in 84% of the cases, compared to only 63% when using mass and isotope information on the M0 alone. We further use, for the first time, automated annotation to evaluate the purity of pseudospectra generated by different metabolomics preprocessing tools, showing that automated annotation can serve as an integrative quality measure for peak picking/deconvolution methods. As an R package, InterpretMSSpectrum integrates flexibly into existing metabolomics pipelines and is freely available from CRAN (https://cran.r-project.org/). KW - Mass Spectrometry KW - Spectra annotation KW - Software KW - R package PY - 2016 UR - https://github.com/cran/InterpretMSSpectrum/ PB - GitHub CY - San Francisco, CA, USA AN - OPUS4-57856 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Sommerfeld, Thomas A1 - Koch, Matthias A1 - Mauch, Tatjana A1 - Jung, Christian A1 - Riedel, Juliane A1 - Lisec, Jan T1 - CRM BAM-A001 eCerto data file N2 - Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-A001 containing Polycyclic Aromatic Hydrocarbons (PAH) in olive oil. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto. KW - Certified reference material KW - Mass spectrometry KW - Olive oil KW - Aromatic hydrocarbons KW - Reference data PY - 2023 UR - https://doi.org/10.5281/zenodo.8380870 DO - https://doi.org/10.5281/zenodo.8380869 PB - Zenodo CY - Geneva AN - OPUS4-58488 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -