Comparison Log
2024-05-26 01:16:13.272001
mwtab Python Library Version: 1.2.5
Source:      https://www.metabolomicsworkbench.org/rest/study/analysis_id/AN000135/mwtab/...
Study ID:    ST000083
Analysis ID: AN000135
Status:      Inconsistent

Sections "MS" contain missmatched items: {('MS_COMMENTS', 'GC-MS raw data files from each Experiment were processed using the Metabolite software, version 2.0.6 beta. Briefly, Agilent.D files were converted to netCDF using Agilent Chemstation, followed by conversion to binary files using Detector. Retention indices of detected metabolites were calculated based on analysis of the FAMEs mixture, followed by their chromatographic alignment all analyses after deconvolution. Metabolites were initially identified by experimental spectra to an augmented version of FiehnLib (i.e., the Agilent Metabolomics Retention Time Locked (RTL) Library, containing spectra and retention indices for over 700 metabolites), using a Metabolite Detector match threshold of 0.6 (combined retention index and spectral probability). All identifications were manually validated to reduce deconvolution errors during data-processing and to eliminate false identifications. The NIST 08 GC-MS was also used to cross validate the spectral matching scores obtained using the library and to provide identifications of unmatched metabolites. The three most fragment ions in the spectra of each identified metabolite were automatically by Metabolite Detector, and their summed abundances were integrated across the elution profile; fragment ions due to trimethylsilylation (i.e. m/z 73 and 147) excluded from the determination of metabolite abundance. Features resulting GC column bleeding were removed from the data matrices prior to further data and analysis.'), ('MS_COMMENTS', 'An Agilent GC 7890A coupled with a single quadrupole MSD 5975C (Agilent Inc.; Santa Clara, CA, USA) was used, and the samples were blocked and analyzed random order for each experiment. Data were collected over the mass range m/z. A mixture of FAMEs (C8-C28) was analyzed once per day together with the for retention index alignment purposes during subsequent data analysis. GC-MS raw data files from each Experiment were processed using the Metabolite software, version 2.0.6 beta. Briefly, Agilent.D files were converted to netCDF using Agilent Chemstation, followed by conversion to binary files using Detector. Retention indices of detected metabolites were calculated based on analysis of the FAMEs mixture, followed by their chromatographic alignment all analyses after deconvolution. Metabolites were initially identified by experimental spectra to an augmented version of FiehnLib (i.e., the Agilent Metabolomics Retention Time Locked (RTL) Library, containing spectra and retention indices for over 700 metabolites), using a Metabolite Detector match threshold of 0.6 (combined retention index and spectral probability). All identifications were manually validated to reduce deconvolution errors during data-processing and to eliminate false identifications. The NIST 08 GC-MS was also used to cross validate the spectral matching scores obtained using the library and to provide identifications of unmatched metabolites. The three most fragment ions in the spectra of each identified metabolite were automatically by Metabolite Detector, and their summed abundances were integrated across the elution profile; fragment ions due to trimethylsilylation (i.e. m/z 73 and 147) excluded from the determination of metabolite abundance. Features resulting GC column bleeding were removed from the data matrices prior to further data and analysis.')}