install_python_dependencies

Uses pip (default) or conda as specified to 
install all required Python modules. The Python packages are installed 
into a virtual Python or conda environment called 'r-DrDimont'. 
The following requirements are installed: numpy, tqdm, python-igraph and ray.
The environment is created with reticulate.

While it has been well established that drugs affect and help
patients differently, personalized drug response predictions remain
challenging. Solutions based on single omics measurements have been proposed,
and networks provide means to incorporate molecular interactions into reasoning.
However, how to integrate the wealth of information contained in multiple omics
layers still poses a complex problem.
We present a novel network analysis pipeline, DrDimont, Drug response prediction
from Differential analysis of multi-omics networks. It allows for comparative
conclusions between two conditions and translates them into differential drug
response predictions. DrDimont focuses on molecular interactions. It establishes
condition-specific networks from correlation within an omics layer that are
then reduced and combined into heterogeneous, multi-omics molecular networks.
A novel semi-local, path-based integration step ensures integrative conclusions.
Differential predictions are derived from comparing the condition-specific
integrated networks. DrDimont's predictions are explainable, i.e., molecular
differences that are the source of high differential drug scores can be retrieved.
Our proposed pipeline leverages multi-omics data for differential predictions,
e.g. on drug response, and includes prior information on interactions.
The case study presented in the vignette uses data published by
Krug (2020) <doi:10.1016/j.cell.2020.10.036>. The package license applies only
to the software and explicitly not to the included data.

Katharina Baum

DrDimont

Drug Response Prediction from Differential Multi-Omics Networks

Pauline Hiort

Julian Hugo

Spoorthi Kashyap

Nataniel Müller

Justus Zeinert

install_python_dependencies function

<dl><dt>package_manager</dt>
<dd>["pip"|"conda"] Package manager to use (default: pip)</dd></dl>

Arguments

Installs python dependencies needed for interaction score computation — install_python_dependencies

<dl>

<dt>package_manager</dt>
<dd>["pip"|"conda"] Package manager to use (default: pip)</dd>

</dl>

install_python_dependencies: Installs python dependencies needed for interaction score computation

Description

Usage

Value

Arguments