Table 1.
Meta-analyses involving untargeted metabolomics-based approaches
Publication title | Data | Technology | Software | Reference |
---|---|---|---|---|
Comprehensive meta-analysis of COVID-19 global metabolomics datasets | 7 datasets from 3 countries, including 5 raw datasets from MetaboLights, MassIVE, and authors, and 2 annotated peak tables from 2 publications. 438 blood samples from 337 subjects | LC/HRMS | MetaboAnalystR 3.0 | Pang et al., Metabolites, 2021 [40] |
Benford’s law and metabolomics: a tale of numbers and blood | Datasets from 3 studies performed by the author, no raw data available, peaktable available for one study | LC/HRMS | No | D'alessandro, Transfus Apher Sci, 2020 [194] |
Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome | 3 LC/MS datasets, no raw data available, one peaktable available (related to the software publication) | LC/HRMS | PAIRUP-MS | Hsu et al., Int J Obes (Lond), 2020 [195] |
MicroRNAs regulating human and mouse naïve pluripotency | Meta-analysis including microRNA-seq, RNA-seq, and metabolomics datasets; the metabolomics datasets are from a single published study; peaktables available; no raw data available | LC/HRMS, LC/QQQ-MS, GC/MS | No | Wang et al., Int J Mol Sci, 2019 [196] |