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.

Documentation

Links