pC-SAC Installation

This guide provides instructions for installing the pC-SAC. pC-SAC is a tool that uses adaptive importance sampling technique with sequential Monte Carlo to generate a set of three-dimensional chromatin chains to enhance low-resolution Hi-C data.

Prerequisites

Before installing pC-SAC, make sure the following dependencies are installed on your system:

• CMake
• Boost
• Eigen

These can typically be loaded on an HPC environment using module commands, like so:

module load cmake
module load boost
module load eigen

Installation

Follow these steps to install pC-SAC:

1. Setup

First, set the main directory where pC-SAC will be installed. Replace /path/to/pCSAC with the actual path on your system.

export MAIN_DIR="/path/to/pCSAC"

2. Download and Install Eigen

Eigen is a dependency for pC-SAC. Download and install it using the following commands:

wget https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.gz
tar xvfz eigen-3.4.0.tar.gz
rm eigen-3.4.0.tar.gz
cd eigen-3.4.0
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=../ -DINCLUDE_INSTALL_DIR=../include/
make install
cd $MAIN_DIR

3. Compile pC-SAC

Edit the CMakeLists.txt in the pC-SAC directory to include the path to the Eigen include directory:

nano ${MAIN_DIR}/CMakeLists.txt
# Modify the include path to /path/to/pCSAC/eigen-3.4.0/include/

Now, compile pC-SAC:

mkdir build
cd build
cmake ..
make

Testing

To verify that pC-SAC has been installed correctly, you can run a test using provided example files:

Files Description

Within the test_toy directory, you will find several example input files required for running pC-SAC. Please explore these files to understand each required input: Additionally, input_generation directory contains Python build functions to generate these files.

• int_mat_seg_len.txt: Length (number of rows) of this file represents the length of any chain for a given reconstruction. Each row represents the amount of DNA in each node (i.e. the radius) of a chromatin chain, either on amstrongs or base-pairs.
• interaction_matrix.txt: Initial low-resolution probabilities.
• test.conf: Configuration file with pC-SAC parameters.

Navigate to the test data directory:

cd ${MAIN_DIR}/script/test_toy

Set the LD_LIBRARY_PATH to include the Boost library path:

export LD_LIBRARY_PATH="/nfs/sw/boost/boost-1.72.0/lib"

Load the Boost module:

module load boost/1.72.0

Run the test:

${MAIN_DIR}/build/bin/chromatin.sis.coarse -conf ${MAIN_DIR}/script/test.conf -prefix test_pCSAC