top of page

  COMPASS A.I. Software

Magellan's machine learning tools help realize the untapped potential of Mass Spec-based OMICs

Thanks to COMPASSS AI software, Mass Spec-based research programs can rapidly extract insights from their data and quickly move to the next study


Learn how... or see a free 'Sandbox' version of our software

COMPASS uses the entirety of your mass spec data, so no finding is missed and confidence in your results is fully supported

COMPASS enhances discovery…


  • Rapidly extracts ALL of the data connected to biological differences

  • Works with even the largest datasets

  • Identifies key molecules without bias towards abundance or familiarity

  • Provides built-in visual outputs that facilitate biological insight

  • Compares signal and noise for confidence that goes beyond standard statistics



…and has many research applications


  • Define molecular differences between the most subtle biological differences

  • Track molecular changes across time or across populations

  • Build OMICs-based machine learning tests for biological differences

  • Use machine learning to stratify subjects based on mass spec-based OMICs

Anchor 1

COMPASS AI:   Introductory Videos

Redefining data scale limits for mass spec-based OMICs

Preventing gaps in Mass Spec-Based OMICs datasets

Avoiding data loss or reduction in Mass Spec-Based OMICs

The Problem with Current Mass Spec Software

PROBLEM: Mass spec data files are large and intractable to rapid analysis at scale 

  • Huge file sizes and proprietary, inaccessible formats

  • Highly technical, focused software solutions

  • Software does not keep pace with instrument output

  • Workflows designed to generate results that are easy to consume, not for maximum insight

THE STATUS QUO: Mass Spec-based OMICs studies are limited in scope

  • Study sizes are highly constrained

  • Studies ignore information-rich data 

  • Data loss and data gaps are accepted

  • Data structure is not tractable for modern A.I. tools

  • Inability to cross-compare data from different studies

Use COMPASS to bring your mass spec research into the information age

Image by Matteo Bernardis

  Solution:      COMPASS


Considers data for all the molecular species instrument identifies


Works for different study designs-- proteomics, lipidomics, and metabolomics, and beyond


Agnostic to instrument and original output data file type


Can work with data (MS1) that are ignored in most other analyses


Considers the data in its entirety, not a selection only


Total integration of mass spec datasets for parallel analysis of proteomics, lipidomics, and metabolomics data


Finds the most biologically relevant information, even if unexpected


Assesses validity of data signals across entire dataset


Turns data into insight in hours, not weeks or months, with visual outputs that allow for easy interpretation of results

Determine if a study generates discernable differences at the outset of analysis


Perform analyses using different parameters to maximize information extraction


Rapidly adjust to the data by altering experimental design or moving to the next study


Uses proprietary computational tools to extract maximum information


Data restructuring is built for machine learning and AI


Designed for analysis of the most complex samples—efforts to reduce sample complexity are unnecessary


Designed for large studies—assess differences in the largest studies

If you have questions or would like to discuss how you could use COMPASS, please reach out below

bottom of page