GENIE BPC Breast Cancer Landscape Manuscript (Sage part)

Overview

An initial descriptive analysis of AACR's GENIE BPC breast cancer cohort. This repo contains only the analysis portions completed by Sage Bionetworks (originally Alex Paynter), destined for merger with an MSK repository later on.

Installation and Setup

To clone this repository, run the following in the command line from a machine with git installed:

git clone https://github.com/Sage-Bionetworks/genie-bpc-brca-landscape-manu/tree/manuscript-minimum

Reproducibility tools

This repository:

• Was tested and run on R version 4.4.2.
• Uses R projects. When running any codes, please open the .RProj file first.
• Does not use renv to manage package environments.
• Does not use docker or other containerization to manage deployment.

The code may work without appreciation of these tools, but no guarantees.

Requirements

To run the code in this respository you will need:

• A Synapse account which has taken the quiz granting data download rights for GENIE (link?)
• The synapser R package, which will also require a python installation (follow instructions at that link).
  • Note: This is only used to acquire the data. It is technically possible to do this manually if needed.

Code structure

The top-level workflow of the project is in main.R. This calls the other analysis scripts in the correct sequence to reproduce my workflow. Other top level folders include:

• /analysis - Scripts (analysis/scripts), quarto/rmarkdown files (analysis/reports) and any other analysis code excluding function definitions.
• /data-raw - Raw data, or as raw as it comes in release.
• /data - Processed data, saved at various stages in the analysis.
• /output - Figures, rendered reports, tables, etc.
• /R - Function definitions. These are sometimes written with {roxygen}-style documentation.

Data

We use GENIE BPC Breast release version 1.2, which is only available to GENIE consortium members. It should closely match the forthcoming Breast 2.0-public release, expected here sometime in the year 2025.

The structure, processing and flow of data is described in detail in the PDF data guide, which will come out with the release.

Acknowledgments/References

We wish to thank the following groups for their upstream contributions to the data:

• AACR Project GENIE team
• Sage bionetworks GENIE team - processing and releases.
• MSKCC biostatistics team
• The patients and institutions who contributed data to the GENIE and GENIE BPC registries.

License

The license for this material is GNU GPLv3. If you want to convince me that allowing closed-source decendents of this project is a better policy, I'm interested in hearing from you. So far I haven't been swayed.