metaboprep

Metaboprep performs standardized pre-analytical processing of metabolomics datasets by extracting data from structured worksheets, computing summary statistics and quality metrics, filtering samples and metabolites with user-defined thresholds, and reporting effects of batch variables to support reproducible metabolomics analyses.

Key Features:

• Standardized Workflow: Applies consistent pre-processing steps to metabolomics data to improve reproducibility and comparability across studies.
• Data Extraction and Characterization: Extracts data from pre-formed structured worksheets and produces comprehensive summary statistics that characterize dataset quality.
• Quality Metrics and Sample/Metabolite Selection: Calculates predefined quality metrics and enables selection or exclusion of samples and metabolites based on those metrics, with support for user-defined thresholds.
• Batch Variable Influence Reporting: Generates reports summarizing quality metrics and the influence of batch variables on the dataset.

Scientific Applications:

• Health-related metabolomics studies: Supports metabolomics analyses in health research by ensuring high-quality, comparable datasets.
• Metabolic pathway and disease association studies: Facilitates reliable interpretation of metabolic pathway perturbations and associations with health and disease.
• Basic and clinical research: Applicable across study types from basic research to clinical applications requiring transparent pre-analytical processing and batch reporting.

Methodology:

Extracts metabolomics data from structured worksheets, applies standardized processing steps, computes summary statistics and quality metrics, filters samples and metabolites using predefined or user-defined thresholds, and produces reports on batch-variable effects.