PraljakReps / pySCA_temp

Python3 implementation of Statistical Coupling Analysis (SCA)

Home Page:https://ranganathanlab.gitlab.io/pySCA

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pySCA

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09.2020

Copyright (C) 2019 Olivier Rivoire, Rama Ranganathan, and Kimberly Reynolds

This program is free software distributed under the BSD 3-clause license, please see the file LICENSE for details.

The current version of the Statistical Coupling Analysis (SCA) analysis is implemented in Python. This directory contains the necessary code for running the SCA calculations, as well examples/tutorials for the dihydrofolate reductase (DHFR) enzyme family, the S1A serine proteases, the small G-protein family and the Beta-lactamase enzyme family. The tutorials are distributed as Jupyter notebooks; for details please see: https://jupyter.org/.

For installation instructions, and an introduction to using the toolbox, please refer to the website:

https://ranganathanlab.gitlab.io/pySCA

or look through the RST files included with the pySCA distribution.

Contents of /

bin/ Executables for running SCA analysis functions
data/ Input data (including those needed for the tutorials)
docs/ HTML documentation (generated by Sphinx)
figs/ Figures used for the notebooks and documentation
notebooks/ Example SCA notebooks
output/ Output files (empty at install, use runAllNBCalcs.sh)
pysca/ Python code for SCA
scripts/ Utility scripts used to generate example data

Contents of bin/

annotateMSA Annotates alignments with phylogenetic/taxonomic information
scaProcessMSA Conducts some initial processing of the sequence alignment
scaCore Runs the core SCA calculations
scaSectorID Defines sectors given the results of the calculations in scaCore

Contents of pysca/

scaTools.py The SCA toolbox - functions for the SCA calculations
settings.py Global configuration settings for the analysis

Contents of notebooks/

SCA_DHFR.ipynb Example for DHFR
SCA_G.ipynb Example for the small G proteins
SCA_betalactamase.ipynb Example for the beta-lactamases
SCA_S1A.ipynb Example for the S1A serine protease

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Python3 implementation of Statistical Coupling Analysis (SCA)

https://ranganathanlab.gitlab.io/pySCA

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