ProfileAnalysis - Statistics and biomarker identification made easy

ProfileAnalysis directly links statistical results with the original LC-MS data, enabling fast on-the-fly identification of potential biomarkers by SmartFormula. SmartFormula combines unique accurate mass and True Isotopic Pattern Analysis (TIP™) information, provided by Bruker´s ESI-TOF or FT-ICR mass spectrometers.

Feature extraction

The sophisticated peak detection algorithm “Find molecular features” extracts all relevant information when mining LC-MS data, even from complex metabolomics datasets. It combines the ions belonging to the same compound into one feature, i.e. isotopes, charge states, adducts or common neutral losses.

Retention time alignment

Metabolic profiling projects can use hundreds or even thousands of samples. An RT alignment algorithm in ProfileAnalysis corrects for possible retention time changes, even for non-linear retention time shifts.

Statistical analyses

The relevant information from complex Metabolomics datasets can be extracted by applying statistical analyses like PCA, PLS, hierarchical clustering, t-test or ANOVA. Implemented result plots like volcano plots, scores and loadings or Receiver operating characteristic (ROC) curves facilitate pinpointing possible biomarkers. ProfileAnalysis also enables easy export of data to statistical software packages like Matlab™, R™ or SIMCA-P™ (Umetrics).

Biomarker identification

SmartFormula enables straightforward identification of potential biomarkers within ProfileAnalysis. Using exact mass and isotopic pattern information, SmartFormula generates elemental formulae that can be queried in public databases like ChemSpider, KEGG* or Metlin via the CompoundCrawler module.

Authorized KEGG Service Provider Logo for 2016

SIMCA-P is a trademark of Umetrix, Umea, Sweden

For Research Use Only. Not for Use in Clinical Diagnostic Procedures.