MAGI - Jobs

MAGI is a tool to quickly find and score consensus between metabolite identifications and gene annotations. Upload FASTA and metabolite files here to begin.

If you found MAGI to be useful for your research, please use the following citation:

Onur Erbilgin, Oliver Rübel, Katherine B Louie, Matthew Trinh, Markus DeRaad, Tony Wildish, Daniel Udwary, Cindi Hoover, Sam Deutsch, Trent R Northen, Benjamin P Bowen. MAGI: A Method for Metabolite Annotation and Gene Integration., ACS Chem Biol. 2019 Apr 19;14(4):704-714. doi: 10.1021/acschembio.8b01107. DOI: 10.1021/acschembio.8b01107 Epub 2019 Apr 4. PMID: 30896917.

Your Job ID is 56a5a67c-e883-4c4b-b4c7-009c9f680e56

Your Job URL is magi.nersc.gov/jobs/?id=56a5a67c-e883-4c4b-b4c7-009c9f680e56

Attention: With the public release of MAGI, many users have noticed extreme sensitivity of MAGI to the exact inchi-key used for original_compound. The table of inchi-keys that we use can be found here https://magifiles.nersc.gov/processed/unique_compounds.csv.gz. We hope to have a generalized solution to these problems soon and apologize for any inconvenience this may cause.

Files (Find Specifications Here)

Personal Information

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MAGI Options

Need example files?

Download here: (.zip)

Additional Parameters

Advanced Search Parameters

MAGI score weights:

Accurate mass search parameters:

Notes