openNAU

openNAU performs preprocessing and analysis of raw mass spectrometry metabolomics data to extract and identify differential metabolic ion peaks and support biomarker discovery in disease studies.

Key Features:

• Data Preprocessing System: Uses the R programming language for preprocessing, normalization, and quality control of raw mass spectrometry datasets.
• Cloud-Based Mass Spectrum Data Analysis: Deploys on a LAMP (Linux+Apache+MySQL+PHP) architecture to provide a scalable cloud environment for mass spectrometry computational tasks.
• Differential Metabolite Identification: Extracts raw mass spectrometry data, performs quality control, and identifies differential metabolic ion peaks to facilitate biomarker discovery.
• Reference Metabolomics Database: Integrates a comprehensive reference database compiled from public sources to improve metabolite identification accuracy.
• Reproducibility and Consistency: Standardizes analytical tools and parameter settings to ensure repeatable and consistent results across studies.

Scientific Applications:

• Oncology metabolomics: Applied in oncology to elucidate tumor mechanisms and identify metabolic markers.
• High-throughput metabolomic studies: Processes large datasets from high-throughput spectrometric data to explore metabolic pathways in cancer and other diseases.

Methodology:

Performs systematic handling from raw mass spectrometry extraction to preprocessing, normalization and quality control in R, identification of differential metabolic ion peaks, integration with a public reference metabolomics database, deployment on LAMP-based cloud computing, and standardization of analytical tools and parameter settings with open-source practices.