Understanding Metastasis Organotropism Patterns Through Within-cell and Between-cells Molecular Interaction Networks

• AUTHOR: João A. I. Miranda¹
• SUPERVISOR: Francisco R. Pinto¹
• CONTACT: jamiranda@ciencias.ulisboa.pt

¹ RNA Systems Biology Lab

Code to reproduce methods & results from my Master's Thesis Project. You can find and download my thesis dissertation at ULisboa Repository.

To reproduce this project just clone or download this repository and create a Python virtual environment. To learn how to create a virtual environment refer to creating a virtual environment.

If you use our data or analysis in your research, please cite us!

System Requirements

Our code was run using the following software:

• Python version 3.10.12
• R version 4.1.2

Python packages to install:

See requirements.txt

To install all packages using this file just type

pip install requirements.txt

inside your python virtual environment.

R packages to install:

To install the IRkernel to run R in notebooks follow these instructions.

Required packages can be installed using notebook 7.

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Analysis notebooks:

The notebooks in the src directory can be used to generate the data required to create all figures in present in the thesis. Just run the notebooks in the following order:

• 1_gene_expression_analysis.ipynb: this Python notebook covers Methods sections 2.2 - 2.5 and subsection 2.7.2 and Results section 3.1.
• 2_organotropism_pairs.ipynb: this Python notebook covers Methods section 2.6 and Results section 3.2.
• 3_intercell_data_analysis.ipynb: this Python notebook covers Methods subsection 2.7.1.
• 4_intercell_networks.ipynb: this Python notebook covers Methods subsections 2.7.3 - 2.7.5 and Results section 3.3.
• 5_intercell_interactions_analysis.ipynb: this Python notebook covers Methods section 2.8 and Results section 3.4.
• 6_intracell_network.ipynb: this Python notebook covers Methods 2.9 and Results section 3.5.
• 7_go_enrichment_analysis.ipynb: this R notebook covers Results subsection 3.5.2.
• 8_cdg_enrichment_analysis.ipynb: this Python notebook covers Results subsection 3.5.1.