This repository contains all of the analysis notebook required for the reproduction of the manuscript Methylome-wide analysis of chronic HIV infection reveals five-year increase in biological age and epigenetic targeting of HLA.
This is a fairly complex analysis pipeline, with many steps. If you are planning of running the entire pipeline starting from raw data, this should be possible with the attached code, but I highly recomend you contact me (the.andrew.gross AT gmail DOT com) for assistance. Its probably not going to run straight though. Some steps in this process have relatively specialized requirements such as high memory machines or use of a compute cluster.
In addition, I have also tried to make available a number of intermediate files which should allow for targeted re-analysis of the data or testing of new hypotheses.
Finally all of the analyses done here are represented in IPython notebooks. This was meant to allow for high level inspection of the analysis logic done for this study. I have done my best to document this such that it can be understood without running the actual code. If you are interesting in reproducing this study, or conducting a similar study I highly recomend looking before you leap into trying to get code to run.
For step by step running instructions see [Guide to Running](./Guide_to_Running.ipynb)
This code uses a number of features in the scientific python stack as well as a small set of standard R libraries. Thus far, this code has only been tested in a Linux enviroment, it may take some modification to run on other operating systems.
I highly recomend installing a scientific Python distribution such as Anaconda or Enthought to handle the majority of the Python dependencies in this project (other than rPy2 and matplotlib_venn). These are both free for academic use.
pip install rpy2 pip install seaborn These are Python packages that I use internally for things such as statistics and visualization. They are all available on my Github page, I recomend downloading them and installing them with python setup.py install. I appoligize for the generic names, I am hoping to develop these a bit more and make them into proper packages up to spec in my next code refactor.