Warpgroup
Warpgroup improves processing of hydrophilic interaction liquid chromatography (HILIC) LC-MS data by detecting peak subregions, determining consensus integration bounds, and performing intelligent missing-value imputation to increase analyte coverage in metabolomics analyses.
Key Features:
- Peak Subregion Detection: Detects chromatographic peak subregions to improve peak identification and quantification in complex LC-MS datasets.
- Consensus Integration Bound Determination: Determines consensus integration bounds across samples to reduce variability in integration regions and improve consistency of quantification.
- Intelligent Missing-Value Imputation: Implements an imputation strategy that rescues signals otherwise lost by naive approaches, increasing analyte coverage.
- XCMS Compatibility: Provides compatibility wrappers for XCMS to integrate Warpgroup processing with existing XCMS-based workflows.
Scientific Applications:
- HILIC LC-MS Metabolomics: Improves detection and quantification in HILIC LC-MS metabolomics datasets, including analyses of Escherichia coli extracts.
- Reduction of Technical Variability: Empirical testing reported halving the coefficient of variation by 19% across replicate injections.
- Increased Analyte Coverage: Refined integration regions and imputation rescue signals and expand coverage in processed datasets.
Methodology:
Implements peak subregion detection, consensus integration bound determination, and intelligent missing-value imputation; implemented in R with compatibility wrappers for XCMS.
Topics
Collections
Details
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Mahieu NG, Spalding JL, Patti GJ. Warpgroup: increased precision of metabolomic data processing by consensus integration bound analysis. Bioinformatics. 2015;32(2):268-275. doi:10.1093/bioinformatics/btv564. PMID:26424859. PMCID:PMC5013975.