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

Abstract

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.

Publication
Bioinformatics
Xiaotao Shen
Xiaotao Shen
Research Scientist

Metabolomics, Multi-omics, Bioinformatics, Systems Biology.

Dr. Si Wu
Dr. Si Wu
Research Scientist
AbbVie
Dr. Liang Liang
Dr. Liang Liang
Research Scientist
Stanford University
Dr. Songjie Chen
Dr. Songjie Chen
Research Scientist
Merck
Prof. Michael Snyder
Prof. Michael Snyder
Professor
Stanford University