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multi-omic-urothelial-anti-pdl1's Introduction

Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

Numbers and Figures Linked to Source Analyses

In the interest of full transparency, please note that calculated numbers and figures are directly linked to their source Jupyter notebooks in this repository throughout our preprint.

Running the Code

To get started, install the requirements:

pip install -r requirements.txt

Create an ENV.sh modeled after ENV_TEMPLATE.sh, pointing to the data that you have available, and then call run.sh to source your ENV.sh in the context of a new Jupyter notebook.

rpy2

Certain notebooks in this repo require rpy2. rpy2 will be installed via the requirements.txt, but depending on your environment may require additional setup.

In order to execute the notebooks, you will need to have:

  1. a functioning R install, preferably of a recent version of R.
  2. certain R libraries commonly used.

Specifically:

# install R, if you haven't already
sudo apt-get install r-base r-base-dev

# create & set personal rlib directory, if not already done
# easiest way to do this is to open an interactive R console, and run 
> options(repos = 'https://cran.rstudio.com')
> install.packages('ggplot2')

## install certain R packages
R -e "options(repos = 'https://cran.rstudio.com'); install.packages(c('dplyr','survival','tidyr','ggplot2'));"

multi-omic-urothelial-anti-pdl1's People

Contributors

tavinathanson avatar

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