View Code on GitHub

Note: To use the Online Sample Classification feature, you'll need to serve this website using a local HTTP server:

# Navigate to the website directory
cd path/to/LT_Website

# Start Python's built-in HTTP server
python -m http.server

# Then visit http://localhost:8000 in your browser
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LifeTracer

Sample Classifier

Classify your samples using our trained machine learning model

Peaks Explorer

Explore detected peaks in the mass spectrometry data

Features Browser

Browse identified molecular features across samples

Feature Groups

Analyze grouped features representing compound families

3D Peak Visualization

Interactive 3D visualization of peak distributions

3D Feature Plots

Explore features in three-dimensional space
Daniel Saeedi1†, Denise Buckner2†, Thomas Walton1, José C. Aponte2*, Amirali Aghazadeh1*
1School of Electrical and Computer Engineering, Georgia Institute of Technology
2NASA Goddard Space Flight Center (GSFC)
*Corresponding authors. Email: jose.c.aponte@nasa.gov, amiralia@gatech.edu
†These authors contributed equally to this work.

With the upcoming sample return missions to the Solar System where traces of past, extinct, or present life may be found, there is an urgent need to develop unbiased methods that can distinguish molecular distributions of organic compounds synthesized abiotically from those produced biotically but were subsequently altered through diagenetic processes. We conducted untargeted analyses on a collection of meteorite and terrestrial geologic samples using two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC×GC-HRTOF-MS) and compared their soluble non-polar and semi-polar organic species. To deconvolute the resulting large dataset, we developed LifeTracer, a computational framework for processing and downstream machine learning analysis of mass spectrometry data. LifeTracer identified predictive molecular features that distinguish abiotic from biotic origins and enabled a robust classification of meteorites from terrestrial samples based on the composition of their non-polar soluble organics.