LINDA

LINDA R-package - Enio GJERGA

This repository contains the scripts for the ILP (Integer Linear Programming) implementation of the LINDA (Linear Integer programming for Network reconstruction using Transcriptomics and Differential splicing data Analysis) R package and accompanying scripts that implement the method. ILP is a mathematical optimisation algorithm in which the objective function and constraints are linear and the variables are integers.

License

Distributed under the GNU GPLv3 License.

Installation

1. Solver Prerequisites

Before installing LINDA, please keep in mind the following solver pre-requisites:

LINDA requires the interactive version of IBM Cplex as an ILP problem optimiser. The IBM ILOG Cplex is freely available through Academic Initiative here.

Once the solvers has been acquired by the user, they must save the executable files in any desired location in the machine they are using and then they can run the LINDA analysis after specifying the solver type (through the solver parameter of the functions, 'cplex' or 'cbc'/'lpSolve' in the future) and the path to the executable file (through the solverPath parameter).

Soon LINDA is also to run by using the open-source Coin-Cbc as well as the lpSolve R-package for smaller case studies.

NOTE: We strongly encourage using CPLEX to solve the LINDA problems since the tool has been mostly maintained by considering CPLEX in mind and also because it showed to be more efficient computationally.

2. Package Depedencies

Additionally before installation, the users must install the following R-package depedencies: igraph, aggregation, XML and aggregation.

3. Package installation

Once the required solvers have been obtained and the mentioned R-package depedencies have been installed, then the users can proceed with the installation of LINDA.

Currently users can install LINDA directly from the source after downloading the source (tar file) and typing in R command line the following:

# directly from GitHub
devtools::install_github("dieterich-lab/LINDA", build_vignettes = FALSE)

# or download the source file from GitHub and install from source
install.packages('path_to_extracted_LINDA_directory', repos = NULL, type="source")

NOTE: If you wish for the the Vignettes to be built and for the test example to run successfully, please put the cplex executable file under the /Downloads/ directory and only then you can set build_vignettes = TRUE.

Running LINDA

The LINDA library can be initialized by:

library(LINDA)

A documentation of the current version of the main runLINDA() function can be obtained by simply typing ?runLINDA in R once the package has been installed.

In a real-case application, depending whether the users are using Transcript Abundance or Exons Skipping data to pinpoint for skipped domains in the analysis, please:

## Load the DIGGER resource with domains mapped to Transcripts:
load(file = system.file("extdata", "digger_human_transcripts.RData", package = "LINDA"))

, or:

## Load the DIGGER resource with domains mapped to Exons:
load(file = system.file("extdata", "digger_human_exons.RData", package = "LINDA"))

Examples

A current example of how to use LINDA over a small Toy test example is ducumented in the vignettes of the package. For this, please check on the LINDA package documentation. Another real case example can be found here