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.