metabolomics-xcms-preprocessing

What problem does it solve?

This Skill automates the complex and time-consuming process of preprocessing raw LC-MS/GC-MS metabolomics data, enabling efficient peak detection, alignment, and feature identification.

Core Features & Use Cases

• Peak Detection: Identifies chromatographic peaks using CentWave or MatchedFilter algorithms.
• Retention Time Alignment: Corrects for temporal drift across samples using Obiwarp.
• Feature Grouping & Gap Filling: Consolidates detected peaks into features and imputes missing values.
• Annotation: Facilitates CAMERA-based adduct and isotope annotation.
• Use Case: Process a batch of LC-MS raw data files to generate a clean feature table ready for downstream statistical analysis and metabolite identification.

Quick Start

Run the XCMS preprocessing workflow on the provided raw data files using default parameters.