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From high resolution accurate mass LC-MS Data to Biological Insight - the MetaboScape Workflow

With Bruker´s MetaboScape, you can quickly pinpoint and identify metabolite markers and use pathway mapping to set them in a biological context after the initial LC-MS/MS data acquisition from UHR-QqTOF instruments using the Instant Expertise™ routine:

  • Extract and combine all relevant information using the advanced T-Rex 3D algorithm
  • Quickly focus on relevant information in complex data set by supervised and non-supervised statistics like PCA, t-test, ANOVA, PLS and bucket correlation analysis
  • Automatically identify known target compounds and seamlessly annotate unknown compounds
  • Use pathway mapping to set identified metabolites in a biological context thereby turning LC-QTOF-MS/MS data into knowledge



Hypothesis and experimental design - Full scan high resolution LC-QTOF-MS/MS data aquisition

Full scan high resolution LC-QTOF-MS/MS data
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Non-targeted data extraction


Extract and combine all relevant Information- T-ReX

The new T-ReX 3D (Time aligned Region Complete eXtraction algorithm automatically extracts all relevant information, even from very complex LC-MS/ MS data sets. It combines ions belonging to the same compound into one feature, i.e. isotopes, charge states, adducts or fragments. Non-linear retention time alignment ensures data consistency even if chromatographic shifts between LC-MS runs occur.

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Sophisticated bucketing, filtering, scaling and normalization to match experimental designs

Sophisticated bucketing, filtering, scaling and normalization to match experimental designs

Region complete extraction by T-ReX 3D ensures features are not missed, which would result in “0” in the bucket table, a critical factor for subsequent statistical analyses of LC-MS/MS data. Different filtering, normalization and scaling options complete the set of data preprocessing tools - a prerequisite for large metabolomics studies.

Data preprocessing

De-replication / Known ID

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Seamless annotation of unknown compounds

Quickly identify relevant information in complex data sets

Using supervised and non-supervised statistics quickly focuses on the relevant information in your data set. Statistics include PCA, t-Test, ANOVA, PLS and bucket correlation analysis combined with dedicated views.

Unknown ID

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Seamless annotation of compounds

Annotation of unknowns by automated molecular formula generation followed by structural assignment through public database queries and in-silico fragmentation of structure candidates.

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Pathway mapping

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Set your results into biological context

The mapping of identified metabolites on metabolic pathway maps using MetaboScape connects experimental data to biology. This can lead to a validated research question, or to formulating a novel hypothesis.

Automatic and confident identification of known compounds

Called de-replication, is essential to fully understand the biological context of metabolomics data. Combing complementary information acquired in positive and negative ionization modes generates deeper insights. Confidence in ID is provided by matching retention time, accurate mass, isotopic pattern information, and MS/MS spectral library spectra according to user definable threshold levels and graphical representation of the achieved “Annotation Quality”.

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