RawHummus

RawHummus: Automated Quality Control Reporting for LC-MS Omics Data

RawHummus generates comprehensive quality control reports for raw LC-MS metabolomics, lipidomics, and proteomics datasets to assess data integrity and analytical performance.

Key Features:

• Automated QC Reporting: Produces QC reports containing plots, tables, and summary statistics of raw data quality metrics.
• Cross-Platform Compatibility: Validated on 13 metabolomics/lipidomics datasets and one proteomics dataset across five LC-MS platforms.

Scientific Applications:

• Analytical Performance Monitoring: Detects detector sensitivity drifts, retention time shifts, and mass accuracy variations in large-scale metabolomics studies.
• Data Quality Assurance: Automates QC assessment to improve reliability and reproducibility of LC-MS analytical results.

Methodology:

Analyzes raw LC-MS data to identify measurement bias, detector sensitivity drift, retention time shift, and mass accuracy variation, generating detailed QC reports for early detection of system inconsistencies prior to downstream data processing.