MS-CleanR

MS-CleanR integrates with MS-DIAL/MS-FINDER to filter and annotate LC-MS feature lists, reducing signal redundancy and improving metabolite identification for downstream metabolomics analyses.


Key Features:

  • MS-DIAL/MS-FINDER integration: Integrates directly with the MS-DIAL/MS-FINDER suite to consume peak lists and leverage annotation functions.
  • Feature filtering: Reduces the number of signals in LC-MS datasets by nearly 80% while preserving 95% of unique metabolite features.
  • Input compatibility: Accepts MS-DIAL peak lists processed through data-dependent analysis (DDA) and data-independent analysis (DIA).
  • Ionization mode support: Supports positive ionization mode (PI), negative ionization mode (NI), or combinations of both.
  • Annotation ranking: Allows ranking of annotation results based on selected databases.
  • Advanced filtering and annotation: Provides advanced functions for filtering and annotating LC-MS features to reduce redundancy and improve annotation quality.

Scientific Applications:

  • Enhanced Metabolite Profiling: Decreases the number of signals by nearly 80% while preserving 95% of unique metabolite features to improve metabolite profiling and data clarity.
  • Pathogen Resistance Studies: Processes MS-DIAL peak lists from DDA and DIA and supports PI and NI modes to support comparative metabolomics relevant to pathogen resistance investigations.

Methodology:

Integrates with the MS-DIAL/MS-FINDER suite to filter and annotate LC-MS features, accepts MS-DIAL peak lists from DDA and DIA in PI and NI modes, and ranks annotation results based on selected databases.

Topics

Details

Tool Type:
library
Programming Languages:
R
Added:
1/18/2021
Last Updated:
3/1/2021

Operations

Publications

Fraisier-Vannier O, Chervin J, Cabanac G, Puech-Pages V, Fournier S, Durand V, Amiel A, André O, Benamar OA, Dumas B, Tsugawa H, Marti G. MS-CleanR: A feature-filtering approach to improve annotation rate in untargeted LC-MS based metabolomics. Unknown Journal. 2020. doi:10.1101/2020.04.09.033308.