metID：一个用于基于 LC-MS 数据的自动化合物注释的 R 包。

metID: an R package for automatable compound annotation for LC-MS-based data.

机构信息

Department of Genetics, Stanford University School of Medicine, Stanford, CA 94304, USA.

Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China.

出版信息

Bioinformatics. 2022 Jan 3;38(2):568-569. doi: 10.1093/bioinformatics/btab583.

DOI:10.1093/bioinformatics/btab583

PMID:34432001

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8722759/

Abstract

SUMMARY

Accurate and efficient compound annotation is a long-standing challenge for LC-MS-based data (e.g. untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developed metID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation. metID is a flexible, simple and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials.

AVAILABILITY AND IMPLEMENTATION

https://jaspershen.github.io/metID.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

基于 LC-MS 的数据（例如非靶向代谢组学和暴露组学）的准确、高效的化合物注释是一个长期存在的挑战。人们已经做出了大量努力来克服这一障碍，但是目前的工具受到所使用的光谱信息源（内部和公共数据库）的限制，并且没有实现自动化和流程化。因此，我们开发了 metID，这是一个 R 包，它结合了所有主要数据库的信息，用于全面、流程化的化合物注释。metID 是一个灵活、简单且强大的工具，可以在所有平台上安装，允许化合物注释过程完全自动化和可重复。在补充材料中提供了详细的教程和案例研究。