README.md

In saezlab/CARNIVAL-Bioconductor-Dev: A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming

This repository is outdated and kept mostly for dt and mult_cond functionalities. Merging them to the main CARNIVAL repository might not be as straightforward since code organization in CARNIVAL-Bioconductor-Dev differs from the main CARNIVAL repository.

CARNIVAL

CARNIVAL is an R-package providing a framework to perform causal reasoning to infer a subset of signalling network from transcriptomics data. This work was originally based on Melas et al. with a number improved functionalities comparing to the original version. Transcription factors’ (TFs) activities and pathway scores from gene expressions can be inferred with our in-house tools DoRothEA & PROGENy, respectively. TFs’ activities and signed directed protein-protein interaction networks +/- drug targets and pathway scores are then used to derive a series of linear constraints to generate integer linear programming (ILP) problems. An ILP solver (CPLEX) is subsequently applied to identify the sub-network topology with minimised discrepancies on fitting error and model size.

More detailed descriptions of CARNIVAL, benchmarking and applicational studies can be found on it's dedicated web-page and in Liu, Trairatphisan, Gjerga et al.:

Liu A, Trairatphisan P, Gjerga E, Didangelos A, Barratt J, Saez-Rodriguez J. (2019). From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL. npj Systems Biology and Applications, https://doi.org/10.1038/s41540-019-0118-z (equal contributions).

Getting Started

A tutorial for preparing CARNIVAL input files starting from differentially gene expression (DEG) and for running the CARNIVAL pipeline are provided as vignettes in R-Markdown, R-script and HTML formats. The wrapper script "runCARNIVAL" was introduced to take input arguments, pre-process input descriptions, run optimisation and export results as network files and figures. Three built-in CARNIVAL examples are also supplied as case studies for users.

Prerequisites

CARNIVAL requires the interactive version of IBM Cplex or CBC-COIN solver as the network optimiser. The IBM ILOG Cplex is freely available through Academic Initiative here. The CBC solver is open source and freely available for any user.

Installing

CARNIVAL is currently available for the installation as an R-package from our GitHub page

# Install CARNIVAL from Github using devtools
# install.packages('devtools') # in case devtools hasn't been installed
library(devtools)
install_github('saezlab/CARNIVAL-Bioconductor-Dev', build_vignettes = TRUE)
# or download the source file from GitHub and install from source
install.packages('path_to_extracted_CARNIVAL_directory', repos = NULL, type="source")

Running CARNIVAL

To obtain the list of tutorials/vignettes of the CARNIVAL package, user can start with typing the following commmand on R-console:

vignette("CARNIVAL-vignette")

License

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

References

Melas et al.:

Melas IN, Sakellaropoulos T, Iorio F, Alexopoulos L, Loh WY, Lauffenburger DA, Saez-Rodriguez J, Bai JPF. (2015). Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury. Integrative Biology, Issue 7, Pages 904-920, https://doi.org/10.1039/C4IB00294F.

DoRothEA v2 - Garcia-Alonso et al.:

Garcia-Alonso L, Ibrahim MM, Turei D, Saez-Rodriguez J. (2018). Benchmark and integration of resources for the estimation of human transcription factor activities. bioRXiv, https://doi.org/10.1101/337915.

PROGENy - Schubert et al.:

Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. (2018). Perturbation-response genes reveal signaling footprints in cancer gene expression. Nature Communication, Issue 9, Nr. 20. https://doi.org/10.1038/s41467-017-02391-6.

Acknowledgement

CARNIVAL has been developed as a computational tool to analyse -omics data within the TransQST Consortium and H2020 Symbiosys ITN Training Network.

"This project has received funding by the European Union’s H2020 program (675585 Marie-Curie ITN ‘‘SymBioSys’’) and the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 116030. The Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA."

saezlab/CARNIVAL-Bioconductor-Dev documentation built on Aug. 30, 2020, 2:39 p.m.