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  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 try 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

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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 â€‹

  • 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

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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

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

Image by Matteo Bernardis

  Solution:      COMPASS

Unbiased

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

Comprehensive

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

Fast

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

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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

Powerful

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

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