Miso: an R package for multiple isotope labeling assisted metabolomics data analysis

MOTIVATION: The use of stable isotope labeling is highly advantageous for structure elucidation in metabolomics studies. However, computational tools dealing with multiple-precursor-based labeling studies are still missing. Hence, we developed Miso, an R package providing automated and efficient data analysis workflow to detect the complete repertoire of labeled molecules from multiple-precursor-based labeling experiments. RESULTS: The capability of Miso is demonstrated by the analysis of liquid chromatography-mass spectrometry data obtained from duckweed plants fed with one unlabeled and two differently labeled tyrosine (unlabeled tyrosine, tyrosine-2H4 and tyrosine-13C915N1). The resulting data matrix generated by Miso contains sets of unlabeled and labeled ions with their retention time, m/z values and number of labeled atoms that can be directly utilized for database query and biological studies. AVAILABILITY AND IMPLEMENTATION: Miso is publicly available on the CRAN repository (https://cran.r-project.org/web/packages/Miso). A reproducible case study and a detailed tutorial are available from GitHub (https://github.com/YonghuiDong/Miso_example). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.