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Models the kinetics of different metabolites in samples over different temperature and time conditions. sampleDrift is able to correct for pre-analytical errors. It predicts pre-centrifugation temperature and time parameters. This tool was tested and approved by external validation of 111 ethylene diamine tetra-acetic acid (EDTA) plasma samples. It improves experimental data by taking into account reproducible pre-analytical, sample history-derived changes in individual metabolite levels, where handling conditions could be predicted from experimental data.
CIMA / Chemical structure-Informed Metabolomics Analysis
A strategy to boost the statistical power of hypothesis testing in metabolomics by incorporating quantitative molecular descriptors for each metabolite. CIMA selects potentially informative summary molecular descriptors and outputs chemical structure-informed false discovery rates. The proposed approach focuses on the general metabolomic hypothesis-testing problem, whereas incorporating structure information into other common metabolomic inference practices, such as multivariate predictive model construction and network inference, is warranted for further research.
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