This repository contains the code used to clean, transform and normalize the data included in the YeastPhenome.org project.
The data and code are stored in the Datasets/ folder and are organized by publication, identified by Pubmed ID. Each <PMID>/ subfolder contains the raw data (i.e., input data obtained from the main text or supplement of the publication, or any other relevant source), a Jupyter notebook containing the code for processing, and the processed data.
The repository also includes a Utils/ folder which contains all auxiliary code and datasets required for processing and normalization.
For more detailed information about the sources of data and the description of processing/transformation steps, see www.yeastphenome.org and the corresponding publication (coming soon).
To run the processing code (code.ipynb), create the following environment:
conda create -n yp-data python=3.7.7 --file requirements.txt
conda activate yp-data
ipython kernel install --user --name=yp-data
To clone the repository:
git clone git@github.com:yeastphenome/yp-data.git
To download only the code/data for a specific publication:
mkdir yp-data
cd yp-data
mkdir Utils
mkdir Datasets
cd Datasets
mkdir <PMID>
Download all contents of the Github Utils/ folder into the local Utils/ and all contents of the Github <PMID>/ folder into the local <PMID>/ (<PMID> is the Pubmed ID of the publication of interest).
Please direct questions & comments to Anastasia Baryshnikova (abaryshnikova@calicolabs.com).