code used for figure generation and statistical analysis for manuscript
This repository contains the necessary Jupyter Notebooks and data files to reproduce analyses and figures in the manuscript.
For example, below is Figure 2 from the manuscript which illustrates the robust separation of autosomal and random allelic X-linked genes from bulk RNA-Seq data allele-specific expression datasets (GTEx). The components of this figure can be generated individually using this repository.
All notebooks to re-create figures are in the notebooks folder of the repo. Each notebook is labeleled according to the corresponding manuscript figure (i.e. figure2.ipynb), which can be used to reproduce figures in the manuscript (minus some minor aesthetic formatting) using the data files in data. All data files are also available in the Supplement of the manuscript. The statistical analyses associated with each figure can be generated alongside the figures in the notebook. Figures in the manuscript were generated with the versions of each library listed below, though more recent versions (if applicable) or slightly older versions will most likely work, as well.
scipy v1.7.1
seaborn v0.11.1
matplotlib v3.0.3
numpy v1.21.3
pandas v1.3.4
jupyter-notebook v5.7.8
One can install Anaconda, which conveniently installs Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.
Alternatively, one can install with pip or conda:
# using pip
pip install -r requirements.txt
# using conda environment
conda create --name <env_name> --file requirements.txt
Simply clone the repository and run a notebook as follows:
git clone https://github.com/quinlan-lab/human-rae-manuscript
cd human-rae-manuscript/notebooks
jupyter notebook figure2.ipynb