Alignment of multiple metabolomics LC-MS datasets from disparate diseases to reveal fever-associated metabolites.

ABSTRACT: Acute febrile illnesses are still a major cause of mortality and morbidity globally, particularly in low to middle income countries. The aim of this study was to determine any possible metabolic commonalities of patients infected with disparate pathogens that cause fever. Three liquid chromatography-mass spectrometry (LC-MS) datasets investigating the metabolic effects of malaria, leishmaniasis and Zika virus infection were used. The retention time (RT) drift between the datasets was determined using landmarks obtained from the internal standards generally used in the quality control of the LC-MS experiments. Fitted Gaussian Process models (GPs) were used to perform a high level correction of the RT drift between the experiments, which was followed by standard peakset alignment between the

SUBMITTER: Nastase AM 

PROVIDER: S-EPMC10399774 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature