COLORS (improving COntact prediction using LOw-Rank and Sparse matrix decomposition) is an approach to seperate the signal from the background in the correlation analysis for protein contacts prediction. In our approach, a correlation matrix was decomposed into two components, i.e., a low-rank component representing background correlations, and a sparse component representing true correlations. Finally the residue contacts were inferred from the sparse component of correlation matrix.
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. https://www.ncbi.nlm.nih.gov/pubmed/26920058
- Install the Eigen library. Plese refere to https://eigen.tuxfamily.org/dox/TopicCMakeGuide.html for details.
- cd COLORS/src; make
./colors input-MSA ouptut-prefix