Metabolomics Data Analysis
Turning complex metabolomics data into meaningful results
Metabolomics analyses typically involve very large sample sets, resulting in the production of complex data outputs. To fully extrapolate meaningful biological information, large sample sets must be run to obtain statistical significance. Metabolomics data analysis typically consists of feature extraction, quantitation, statistical analysis and compound identification.
The Thermo Scientific™ metabolomics software suite is specifically designed to mine complex HRAM Orbitrap data, converting large datasets into meaningful results.
Metabolomics data analysis consists of feature extraction, quantitation, statistical analysis, compound identification and biological interpretation. Thermo Scientific™ Compound Discoverer™ software addresses the challenges of turning large and complex biological data sets into knowledge. Combined with powerful visualization tools, Compound Discoverer quickly finds and identifies the differences that matter.
Metabolite identification is by far the most challenging step in metabolomics research. m/zCloud is a state-of-the-art online mass spectral database that features a freely searchable collection of HRAM spectra using a new third generation spectral correlation algorithm.
Thermo Scientific™ TraceFinder™ software makes the challenging steps of unknown screening and targeted quantitation of metabolites simple, fast and productive. It is the only software that can be used to develop methods, acquire and process data, and generate reports with the full portfolio of Thermo Scientific quantitative mass spectrometers (both HRAM Orbitrap and triple quadrupoles).
Thermo Scientific™ LipidSearch™ software processes both HRAM Orbitrap and SRM triple quad data for the automatic identification and quantification of cellular lipids. It also automatically integrates complex data into reports to dramatically reduce data analysis time.