Published February 28, 2022 | Version v1
Dataset Open

A benchmarking dataset for peak detection methods in untargeted metabolomics using LC/HRMS

Authors/Creators

  • 1. Icahn School of Medicine at Mount Sinai

Contributors

  • 1. Icahn School of Medicine at Mount Sinai

Description

Randomly selected 20,000 mz and rt pairs were manually evaluated for true positive and true negative signals in a single LC/HRMS data file (003.mzML) from the study MTBLS1684. The data file was processed using four peak detection methods - IDSL.IPA, XCMS, MZMINE and MSDIAL. 

Files

idslipa_benchmarking_dataset.csv

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Additional details

Related works

Is derived from
https://www.ebi.ac.uk/metabolights/MTBLS1684 (URL)