4. Code Installation

4.1. Download Mistic

  • pip install mistic

  • To download Mistic’s code repository, perform one of the three options:

    • Download the code repository from link.

    • Open a Terminal and at the command line, type:

    $ git clone https://github.com/MathOnco/Mistic.git

    • Code can also be downloaded from Zenodo.

4.2. Preload user data

  • In the Mistic folder, navigate to /user_inputs folder to upload input files:

    • Mistic_code/code/user_inputs/

    • Use the /figures folder to upload the multiplexed images

      • Example NSCLC Vectra dataset is available from Zenodo_data.

    • Use the /metadata folder to upload the markers.csv and imaging markers of interest as Markers_ids.csv

      • Example files are provided in the subfolders: Vectra, CyCIF, t-CyCIF and CODEX

      • Move the files from the relevant subfolder into the /metadata folder

      • Note: For the Stack Montage option, only the markers.csv file is required.

    • (Optional) Use the /metadata folder to

      • Upload image tSNE co-ordinates as X_imagetSNE.csv

        • If no user-generated tSNE co-ordinates are provided, Mistic will generate a set of t-SNE coordinates to render the images

      • Upload image metadata such as

        • Cluster labels as Cluster_categories.csv

          • If cluster labels are not provided, Mistic will cluster the images using a Bayesian mixture model.

        • Patient_ids as Patient_ids.csv

        • Treatments as Treatment_catgories.csv

        • Patient response as Response_categories.csv

        • If any of these are unavailable, Mistic will use either the randomly-generated or user-provided tSNE points without any color coding i.e. dots are colored in gray.

        • Sample metadata files are provided for reference in separate subfolders for each imaging technique (Vectra, CyCIF, t-CyCIF and CODEX) in the /metadata folder

        • If using the sample metadata, move the files from the relevant subfolder into the /metadata folder

4.3. Run Mistic