wangx677 / safepy

Python implementation of Spatial Analysis of Functional Enrichment (SAFE)

INTRODUCTION

SAFE (or Spatial Analysis of Functional Enrichment) is an automated network annotation algorithm. Given a biological network and a set of functional groups or quantitative features of interest, SAFE performs local enrichment analysis to determine which regions of the network are over-represented for each group or feature. SAFE visualizes the network and maps the detected enrichments onto the network.

SAFE was originally implemented in MATLAB and stored at https://bitbucket.org/abarysh/safe/. However, as of early 2017, the MATLAB implementation is only maintained for legacy purposes. New work related to SAFE is moving to Python and this repository.

WARNING. This package is still in development. Please use caution.

GETTING STARTED

SAFE requires Python 3 and a set of packages listed in extras/requirements.txt. We recommend setting up a virtual environment and installing all the required packages via pip:

cd safepy/
virtualenv -p python3.6 safepy_env
source safepy_env/bin/activate
pip install -r extras/requirements.txt

After the installation is complete, it is useful to run a "hello world" SAFE analysis using the Jupyter notebook at examples/Usage_examples.ipynb.

To do so, from within the safepy_env environment install a new ipython kernel:

ipython kernel install --user --name=safepy

Then start jupyter, open examples/Usage_examples.ipynb and select the safepy kernel.

jupyter-notebook

To run the examples, several common datasets will be required (e.g., the genetic interaction similarity network from Costanzo et al., 2016). These datasets are stored separately at https://github.com/baryshnikova-lab/safe-data (to avoid duplication with other SAFE-related repositories and packages). We recommend cloning the safe-data repository and storing it locally (e.g., at <path_to_safe-data_folder>). In addition, it is necessary to edit the SAFE settings file (at safepy/safe_default.ini) with the path to the safe-data folder.

vim safe_default.ini
...
[DEFAULT]
safe_data = <path_to_safe-data_folder>
...

HELP

Please direct all questions/comments to Anastasia Baryshnikova ([email protected]).

The main repository for this code is at https://github.com/baryshnikova-lab/safepy. Please subscribe to the repository to receive live updates about new code releases and bug reports.

HOW TO CITE

The manuscript describing SAFE and its applications is available at:

Baryshnikova, A. (2016). Systematic Functional Annotation and Visualization of Biological Networks. Cell Systems. http://doi.org/10.1016/j.cels.2016.04.014