pyfferaph 0.0.1a4

PYthon Functions For Extended, Reproducible Analysis and graPH

Installation

conda create -n pyfferaph python=3.6
conda activate pyfferaph

On linux:

pip install --upgrade pyfferaph

On Mac/Windows, you need first to install the dependencies.

conda install -c conda-forge MDAnalysis
pip install --upgrade pyfferaph

# filter_pyff
# ============
#
# filter_pyff script works on adjacency matrix files, such as as those outputted by Pyinteraph (add reference)
# The script is designed to:

#1) return and save to file a macro_iin.dat file starting from separete interaction matrices (salt bridges, hydrogen bonds, hydrophobic interactions)
# Each interaction in each interaction matrix is retained only if above a certaint treshold value (-p option) if provided (default value 0.0).
# The filtered matrices arte then combined to generate a macro_iin.dat file,
# an edge between two nodes is drawn if that interaction is above treshold in at least one filterd interaction matrix

threshold=5.0
filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $threshold -o out_macro_iin.dat

#2) Generate an intercation network G based on either separate interaction matrices or a macro IIN file. A topology file is required (option -g)
# compute all shortest paths between a set of source and target residues defined in a json formatted input file (option -z).
# A json-formatted file can be obtained with:

filter_pyff -j template.json

# A score is assigned for each path of a given source-target pair.
# Identify the best path (or equally best pahts) among all paths connecting source and target residues
# Calculate the communication robustness index for each source-target pathway (a pathway is define as the set of all the shortest paths connecting source and taget)
# Print to file all the above mentioned informations. The script saves one file for each source residue. Eache file contains all patht between that source and all the target resiudes.

#starting from separete interaction matrices:

filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $treshold -o out_macro_iin.dat -g topol.gro -z z_file.json

#starting from a macro_iin.dat file

filter_pyff -i macro_iin.dat -g topol.gro -z z_file.json

#3) Compute the selective betweeness for a given redidue (option -s) considering all shortest path between a given source and target file (option -t)

filter_pyff -d sb_graph.dat -d hb_graph.dat -d hc_graph.dat -p $treshold -o out_macro_iin.dat -g topol.gro -s RES1 -t RES2 RES3

#or

filter_pyff -i macro_iin.dat -g topol.gro -s RES1 -t RES2 RES3