Dataset of the comprehensive description and methodological validation for an in-depth targeted metabolomics platform developed by Yin Lab

In the dataset, we descibed the detail information for our newly proposed in-depth target-based metabolome platform through an integration of six distinct conditions, including a normal phase, a pre-column chemical derivatization and four reversed phase separation methods for the quantification of small molecules (32 sub-classes) in serum. Quantification of each metabolite was achieved after normalization using isotope-labeled internal standards. In addition, the methodological validation results were presented in the dataset as well.