METASPACE
METASPACE annotates metabolites in high-mass-resolution imaging mass spectrometry (IMS) datasets, providing FDR-controlled molecular sum formula identification and spatial localization within tissues, cell cultures, and agar plates at cellular resolution.
Key Features:
- FDR-controlled annotation: Performs false discovery rate control for metabolite annotation at the molecular sum formula level.
- Metabolite-signal match score: Uses a scoring system that quantifies the match between observed signals and known metabolites.
- Target-decoy FDR estimation: Implements a target-decoy approach to estimate FDR specifically for spatial metabolomics data.
- Automated metabolite identification: Automates identification and annotation of hundreds of metabolites in IMS datasets.
- Cellular-resolution spatial localization: Localizes metabolites within tissues, cell cultures, and agar plates at cellular resolution.
- Cloud-based computational engine: Provides scalable computational resources for processing high-mass-resolution IMS data.
Scientific Applications:
- Spatial metabolomics: Enables mapping of metabolite distributions in tissues, cell cultures, and agar plates to investigate cellular processes and disease mechanisms.
- Imaging mass spectrometry analysis: Supports annotation and interpretation of high-mass-resolution IMS datasets for molecular localization studies.
Methodology:
Performs FDR-controlled annotation at the molecular sum formula level using a metabolite-signal match score combined with target-decoy FDR estimation.
Topics
Details
- License:
- Apache-2.0
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python, JavaScript, Shell, Other
- Added:
- 11/20/2021
- Last Updated:
- 11/24/2024
Operations
Publications
Palmer A, Phapale P, Chernyavsky I, Lavigne R, Fay D, Tarasov A, Kovalev V, Fuchser J, Nikolenko S, Pineau C, Becker M, Alexandrov T. FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry. Nature Methods. 2016;14(1):57-60. doi:10.1038/nmeth.4072. PMID:27842059.
DOI: 10.1038/nmeth.4072
PMID: 27842059