Statistical Coupling Analysis in Python.¶
The Statistical Coupling Analysis (SCA) is an approach for characterizing the pattern of evolutionary constraints on and between amino acid positions in a protein family. Given a representative multiple sequence alignment of the family, the analysis provides methods for quantitatively measuring the overall functional constraint at each sequence position (the position-specific, or “first-order” analysis of conservation), and for measuring and analyzing the coupled functional constraint on all pairs of sequence positions (the pairwise-correlated, or “second-order” analysis of conservation). The premise is that extending the traditional definition of conservation to include correlations between positions will contribute to defining the architecture of functional interactions between amino acids, and more importantly, help define the basic physical principles underlying protein structure, function, and evolution.
Rivoire, O., Reynolds, K. A., and Ranganathan, R. Evolution-Based Functional Decomposition of Proteins. PLOS Computational Biology 12, e1004817 (2016).
I. Installing and Using pySCA¶
- Getting Started
- File and Directory Structure
- 1. Constructing and annotating a multiple sequence alignment
- 2. Alignment pre-processing and conditioning
- 3. Calculation of the conservation and co-evolution statistics
- 4. Identifying significant evolutionary correlations
- 5. Interpretation of the results and sector definition
- The pySCA Code