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Untargeted Metabolomics Feature Clustering

This page contains the supporting files for the paper VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography - Mass Spectrometry Data by Alkhalifah et al. (2019).

  • data contains the files that are required to be uploaded into the VOCCluster, DBSCAN and OPTICS. Generated files from the algorithms are stored in the data folder.

  • DBSCAN contains DBSCAN algorithm that is coded in Python. DBSCAN has been tuned to cluster deconvoluted GCMS data. It will not cluster more than one VOC from a sample in a cluster.

  • OPTICS contains OPTICS algorithm that is coded in Python. OPTICS has been tuned to cluster deconvoluted GCMS data. It will not cluster more than one VOC from a sample in a cluster.

  • VOCCluster contains VOCCluster algorithm that is coded in Python. It is a novel clustering technique that is able to cluster similar VOCs from different deconvoluted DCMS breath data.

  • Note: All of the algorithms read the required files from data folder to generate clusters for the given data.

Checking out the whole project

Use the following command to clone the whole repository. This will give you all the executables, input_data and evaluation scripts used in the paper.

git clone https://github.com/Yaser218/Untargeted-Metabolomics-Clustering.git

Important note:

  • Large files were uploaded using git lfs. To install git lfs, visit https://git-lfs.github.com.

  • After git lfs is instaled, pull large fils after downloading the project, use the following command in your terminal:

      git lfs pull
    

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VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography - Mass Spectrometry Data

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