DAA_for_Moonlight2R

Differential abundance analysis for Moonlight2R

Introduction

This repository contains:

• A folder cptac_data_access/ which includes a script for the access to quantitative proteomic data of tumor and normal samples of different cancer types from CPTAC Data Portal and for data visualization.

Requirments

To reproduce the results follow these steps:

• Clone the github repository

git clone https://github.com/ELELAB/DAA_for_Moonlight2R.git

• create a new environment as follows:

module load conda
conda create --prefix ./DAA_env python=3.11 r-base=4.3

• activate the environment

conda activate DAA_env/

• to run the scripts make sure to install these packages in the environment as follows:

    conda install pandas
    conda install numpy
    conda install matplotlib
    conda install seaborn
    conda install scikit-learn
    pip install cptac