ReDU: a framework to find and reanalyze public mass spectrometry data

Alan K. Jarmusch, Mingxun Wang, Christine M. Aceves, Rohit S. Advani, Shaden Aguirre, Alexander A. Aksenov, Gajender Aleti, Allegra T. Aron, Anelize Bauermeister, Sanjana Bolleddu, Amina Bouslimani, Andres Mauricio Caraballo Rodriguez, Rama Chaar, Roxana Coras, Emmanuel O. Elijah, Madeleine Ernst, Julia M. Gauglitz, Emily C. Gentry, Makhai Husband, Scott A. JarmuschKenneth L. Jones, Zdenek Kamenik, Audrey Le Gouellec, Aileen Lu, Laura Isobel McCall, Kerry L. McPhail, Michael J. Meehan, Alexey V. Melnik, Riya C. Menezes, Yessica Alejandra Montoya Giraldo, Ngoc Hung Nguyen, Louis Felix Nothias, Mélissa Nothias-Esposito, Morgan Panitchpakdi, Daniel Petras, Robert A. Quinn, Nicole Sikora, Justin J.J. van der Hooft, Fernando Vargas, Alison Vrbanac, Kelly C. Weldon, Rob Knight, Nuno Bandeira, Pieter C. Dorrestein*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

66 Citations (Scopus)

Abstract

We present ReDU (https://redu.ucsd.edu/), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one’s own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Original languageEnglish
Pages (from-to)901-904
Number of pages4
JournalNature Methods
Volume17
Issue number9
DOIs
Publication statusPublished - Sept 2020

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