Run EPIC

The EPIC toolkit was initially published here: Hu, L. Z., et al. “EPIC: software toolkit for elution profile-based inference of protein complexes.” Nature methods 16.8 (2019): 737-742. Link to the publication

Forked from the orignial repository, I have created RunEPIC to provide the code to run EPIC locally.

1. Environment

The main function in EPIC was implemented in Python, given the headache caused by various libraries, the Anaconda enrionment was used. Simply install Anaconda Python 2.7 version for your convience, and we will start from there.

2. Prerequisite

Let’s create the virtual enrionment:

path to the anaconda directory/bin/conda create -n EPIC python=2.7 anaconda

then we need step up some chanels:

(EPIC)conda config --add channels defaults
(EPIC)conda config --add channels bioconda
(EPIC)conda config --add channels conda-forge

get R installed:

(EPIC)conda install r

start R:

(EPIC)R

install wccsom for computing WCC scores:

> install.packages("kohonen")
> install.packages("https://cran.r-project.org/src/contrib/Archive/wccsom/wccsom_1.2.11.tar.gz",
                 type = "source")
> q()

install conda packages:

conda install requests scikit-learn beautifulsoup4 mock numpy rpy2
python -mpip install -U matplotlib

lastly, make sure Java is installed, so that ClusterOne.jar could be used.

3. Run EPIC

git clone https://github.com/zqzneptune/RunEPIC.git

The main.py in EPIC implemented all the functions:

python directory to RunEPIC/src/main.py \
       -s 11101001 \
       [Directory to Input Folder/] \
       -c [path to the gold standard file ] \
       [Directory to Output Folder/] \
       -o PrefixName \
       -M RF \
       -n 6 \
       -m COMB \
       -f STRING