kinact

Toolbox for Kinase Activity Scoring

This repository collects different computational methods to infer kinase activities from phosphoproteomics datasets. Each method will be accompanied by a protocol for explanation and in order to enable transfer to other datasets.

The package has been implemented by Jakob Wirbel in the Saez-Rodriguez Group at RWTH-Aachen.

Please be aware that the package is under on-going development.

Licence

Distributed under the GNU GPLv3 License. See accompanying file LICENSE.txt or copy at http://www.gnu.org/licenses/gpl-3.0.html

Installation

Mac/Linux Users

In order to use kinact, open a command line/terminal. You can clone the repository and install the package with

git clone https://github.com/saezlab/kinact.git
cd kinact
python setup.py install

Windows Users

working on it :)

Trouble?

Please use the GitHub Issue tracker if you run into any trouble or if you have feature requests. We will work on them as fast as possible.

Quick start

The package contains example data from a publication by de Graaf et al., in which the phosphoproteome of Jurkat T-cells after prostaglandin E2 stimulation was analysed. The data can be loaded with:

import kinact
data_fc, data_p_value = kinact.get_example_data()
print data_fc.head()

             "5min"     "10min"    "20min"    "30min"    "60min"
ID
A0AVK6_S71   −0.319306  −0.484960  −0.798082  −0.856103  −0.928753 
A0FGR8_S743  −0.856661  −0.981951  −1.500412  −1.441868  −0.861470 
A0FGR8_S758  −1.445386  −2.397915  −2.692994  −2.794762  −1.553398
A0FGR8_S691   0.271458   0.264596   0.501685   0.461984   0.655501 
A0JLT2_S226  −0.080786   1.069710   0.519780   0.520883  −0.296040

Prior-knowledge information about kinase-substrate interactions can be loaded from the pypath package (see also the documentation or the github repository). Per default, interactions from PhosphoSitePlus and Signor are loaded, but other sources from pypath can be specified with the sources parameter of the function. For kinase-substrate interactions from other organisms, specify organim='yeast' or organism='mouse' in the function call.

adjacency_matrix = kinact.get_kinase_targets()

Finally, estimation of the kinase activities can be performed as follows for the example of the KSEA protocol:

scores, p_values = kinact.ksea.ksea_mean(data_fc=data_fc["5min"].dropna(),
                                         interactions=adjacency_matrix,
                                         mP=data_fc["5min"].values.mean(),
                                         delta=data_fc["5min"].values.std())

Methods included in kinact:

• KSEA

  KSEA is a method for the inference of kinase activities from phosphoproteomics data based on kinase substrate sets, which are constructed from curated information about kinase-substrate interactions from public resources like PhosphoSitePlus. The values of the fold changes of the phospho-sites in the substrate set of a given kinase are used to compute a score for the activity of this kinase. The main scoring system for KSEA is the mean or the median of the fold changes in the substrate set. KSEA was first proposed in the publication from Casado et al..

• to be extended