Comparison Log
2026-03-15 08:16:59.596826
mwtab Python Library Version: 2.0.0
Source:      https://www.metabolomicsworkbench.org/rest/study/analysis_id/AN007762/mwtab/...
Study ID:    ST004603
Analysis ID: AN007762
Status:      Inconsistent

Sections "MS" contain missmatched items: {'MS_COMMENTS': ["The data underwent processing through MetaboScape ® 4.0 software (Bruker, Bremen, Germany). In the T-ReX 2D/3D workflow, specific settings were applied for molecular feature detection, including a minimum intensity threshold of 1,000 counts, a maximum peak duration of seven spectra, and a maximum peak area. Mass recalibration was conducted within a retention time range of 0 to 0.3 minutes, and only features present in at least six of the 24 samples per cell type were considered. The MS/MS import method was set to be averaged. Bucketing parameters for the data were defined with a retention duration of 0.3 to 25 minutes and a mass range of 50 to 1,000 m/z. Metabolite identification involved comparing combined MS/MS, precursor m/z values, and isotope pattern scores to the human metabolome database (HMDB) 4.0. The annotation quality score (AQ score) played a crucial role in selecting the best matching feature when multiple features corresponded to a given database entry. For further analysis, metabolite data were saved as CSV files and integrated into the comprehensive metabolomics platform MetaboAnalyst 6.0 software (https://www.metaboanalyst.ca, Accessed: 1st of February 2024). The identification of significantly altered metabolites in the group treated with MGB compounds, in comparison to the standard control group, was accomplished using a two-tailed independent Student's t-test. This process led to the creation of a volcano plot, visually illustrating the statistical significance and fold change (p<0.05*, FC=1.25), thereby highlighting the alteration of cellular metabolites under each condition. Furthermore, each medication underwent one-way analysis of variance (ANOVA) to pinpoint significantly different metabolites from the control group. Additionally, box plots illustrating statistically altered cellular metabolites were generated. Multiple groups were compared using ANOVA, with the same significance threshold set at p-value < 0.05 and fold change = 1.25. MetaboAnalyst 6.0 software was also utilized for enrichment analysis, joint pathway analysis, and Partial Least Squares-Discriminant Analysis (PLS-DA) to compare the two groups. False discovery rate was implemented to eliminate false positives and address multiple hypothesis testing (FDR).", "The data underwent processing through MetaboScape ® 4.0 software (Bruker, Bremen, Germany). In the T-ReX 2D/3D workflow, specific settings were applied for molecular feature detection, including a minimum intensity threshold of 1,000 counts, a maximum peak duration of seven spectra, and a maximum peak area. Mass recalibration was conducted within a retention time range of 0 to 0.3 minutes, and only features present in at least six of the 24 samples per cell type were considered. The MS/MS import method was set to be averaged. Bucketing parameters for the data were defined with a retention duration of 0.3 to 25 minutes and a mass range of 50 to 1,000 m/z. Metabolite identification involved comparing combined MS/MS, precursor m/z values, and isotope pattern scores to the human metabolome database (HMDB) 4.0. The annotation quality score (AQ score) played a crucial role in selecting the best matching feature when multiple features corresponded to a given database entry. For further analysis, metabolite data were saved as CSV files and integrated into the comprehensive metabolomics platform MetaboAnalyst 6.0 software (https://www.metaboanalyst.ca, Accessed: 1st of February 2024). The identification of significantly altered metabolites in the group treated with MGB compounds, in comparison to the standard control group, was accomplished using a two-tailed independent Student''s t-test. This process led to the creation of a volcano plot, visually illustrating the statistical significance and fold change (p<0.05*, FC=1.25), thereby highlighting the alteration of cellular metabolites under each condition. Furthermore, each medication underwent one-way analysis of variance (ANOVA) to pinpoint significantly different metabolites from the control group. Additionally, box plots illustrating statistically altered cellular metabolites were generated. Multiple groups were compared using ANOVA, with the same significance threshold set at p-value < 0.05 and fold change = 1.25. MetaboAnalyst 6.0 software was also utilized for enrichment analysis, joint pathway analysis, and Partial Least Squares-Discriminant Analysis (PLS-DA) to compare the two groups. False discovery rate was implemented to eliminate false positives and address multiple hypothesis testing (FDR)."]}
'Metabolites' section of 'MS_METABOLITE_DATA' block do not match.
'Data' section of 'MS_METABOLITE_DATA' block do not match.