Department of Plant Sciences, Weizmann Institute of Science, Rehovot, Israel.
Department of Analytical chemistry, Israel Institute for Biological Research, Ness Ziona, Israel.
Bioinformatics. 2019 Sep 15;35(18):3524-3526. doi: 10.1093/bioinformatics/btz092.
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.
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.
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 data are available at Bioinformatics online.
在代谢组学研究中，使用稳定同位素标记具有高度的优势。然而，处理基于多前体标记研究的计算工具仍然缺失。因此，我们开发了 Miso，这是一个 R 包，提供了自动化和高效的数据分析工作流程，用于从基于多前体标记的实验中检测完整的标记分子谱。
Miso 的能力通过分析喂食了一种未标记和两种不同标记的酪氨酸（未标记的酪氨酸、酪氨酸-2H4 和酪氨酸-13C915N1）的浮萍植物的液相色谱-质谱数据得到了证明。Miso 生成的数据矩阵包含未标记和标记离子的集合，它们的保留时间、m/z 值和标记原子的数量可直接用于数据库查询和生物学研究。
Miso 可在 CRAN 存储库（https://cran.r-project.org/web/packages/Miso）上公开获得。可从 GitHub（https://github.com/YonghuiDong/Miso_example）获得可重现的案例研究和详细的教程。
补充数据可在生物信息学在线获得。
