pips is a Python software package written by Jesse Bloom. pips source code is available on GitHub.

This program is designed to analyze phylogenies to identify potentially stabilizing mutations.

The references for pips are:

• Jesse D. Bloom, Jagannath S. Nayak, and David Baltimore. "A computational-experimental approach identifies mutations that enhance surface expression of an oseltamivir-resistant influenza neuraminidase." PLoS One. 6:e22201 (2011) http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0022201
• Jesse D. Bloom and Matthew J. Glassman. “Inferring stabilizing mutations from protein phylogenies: application to influenza hemagglutinin.” PLoS Comput. Biol. 5:e1000349 (2009) http://www.ncbi.nlm.nih.gov/pubmed/19381264

pips is a Python package. It requires the following:

• Python: pips has been tested with Python version 2.6* and 2.7*. It is not known if pips will work with other versions of Python.
• numpy
• gcc or some similar C compiler is required to build the C extensions.
• Either scipy or the Python transcendental package are required. Originally, pips used transcendental, but this no longer appears to be available on the web, so you might need to use scipy.

Download pips from the repository on GitHub. Build and install pips with the following commands:

python setup.py build
python setup.py install

The last command might need to be replaced with:

sudo python setup.py install

if you want to install globally and do not have superuser privileges by default, or by:

python setup.py install --user

if you want to install locally.

Installing pips will install all the modules, which you can then import in Python.

It also installs the following scripts, which are found in the ./scripts/ subdirectory of the main pips package. These scripts are:

pips_analysis.py
pips_correlate_selected_mutations.py
pips_analyze_selected_mutations.py
pips_run_cupsat.py
pips_build_tree_and_alignment.py
pips_run_foldx.py
pips_consensus.py

Unfortunately, these scripts are not currently documented externally. However, if you look in the documentation string at the beginning of each script, it will explain how to create an input file appropriate for running the script.

The pips package also contains an ./examples/ subdirectory that shows example analyses -- these may also be helpful.