<1>Installation

step1: Install Eigen, a C++ library for calculating SVD. 
Eigen can be download from https://bitbucket.org/eigen/eigen/get/3.2.6.tar.bz2

step2: Complie COLORS using the following command:
g++ -o colors main.cpp colors.h colors.cpp matrix.h matrix.cpp sequence.h sequence.cpp type.h -O3 -Iyour_eigen_install_dir/include/eigen 

Please replace your_eigen_insall_dir with the directory you specificed in step1.


<2>Usage

./colors msa-file output-prefix

The MSA is represented by a M by N matrix, where M is the number of sequences and N is the length of the target.

COLORS will output 6 files: output-prefix.mi_lrs, output-prefix.omes_lrs, output-prefix.cov_lrs, output-prefix.mi_score, output-prefix.omes_score and output-prefix.cov_score. 

output-prefix.mi_lrs is the sparse matrix calculated by COLORS given the original MI matrix.
output-prefix.mi_score has 5 columns: position_i, position_j, original_score, apc_score and lrs_score.

<3>Contact and Citation 

Haicang Zhang, Yujuan Gao, Minghua Deng, Chao Wang, Jianwei Zhu, Shuai Cheng Li, Wei-Mou Zheng, Dongbo Bu. Improving residue–residue contact prediction via low-rank and sparse decomposition of residue correlation matrix. Biochemical and biophysical research communications 472.1 (2016): 217-222.