William Choi-Kim and Sayed-Rzgar Hosseini
Tumorigenesis is a stepwise process that is driven by a sequence of molecular changes forming pathways of cancer progression. Conjunctive Bayesian Networks are probabilistic-graphical models designed for the analysis and modeling of these pathways [1]. CBN models have evolved into different varieties such as CT-CBN [2], H-CBN [3], B-CBN [4] and R-CBN [5] each addressing different aspects of this task. However, the software corresponding to these methods are not well-integrated as they are implemented in different languages with heterogeneous input and output formats. This necessitates a unifying platform that integrates these models and enables standardization of the input and output formats to facilitate the downstream pathway analysis and modeling. Evam-tools [6] is an R package, which has taken the initial steps towards this end. However, it partially serves this purpose, as it does not include the B-CBN model and the recently developed R-CBN algorithm, which focuses on the robust inference of cancer progression pathways [5]. Importantly, the B-CBN and R-CBN algorithms for pathway quantification require exhaustive consideration and weighting of all the potential dependency structures (posets) within mutational quartets. This entails re-implementation of the CBN models and adjustment of the downstream pathway analysis and modeling functions. Therefore, here we introduce CBN2Path R package that not only includes the original implementation of the CBN models (e.g. CT-CBN and H-CBN) in a unifying interface, but it also accommodates the necessary modifications to support the robust CBN algorithms (e.g. B-CBN and R-CBN). In summary, CBN2Path is an R package that supports robust quantification, analysis and visualization of cancer progression pathways from cross-sectional genomic data, and so we anticipate that it will be a widely-used package in the future.
To install the CBN2Path R package, you first need to install the
gsl:
Install GSL with homebrew on Mac:
If you don’t have homebrew, run the following command in your terminal/console:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"Then, also in terminal:
brew install gslNote that if gsl was installed using any method other than Homebrew,
you need to uninstall gsl, and then reinstall it using Homebrew (see
https://brew.sh if you have not installed Homebrew yet).
Install GSL on Linux:
In your shell:
sudo apt-get install libgsl-devOn Linux, if the ggraph dependency fails, run the following in your
shell:
sudo apt install libfontconfig1-devThis appears to fix a sysfonts issue. We’re not sure why this is necessary.
On Windows, we suggest installing RTools (which includes a distribution of GSL):
Download RTools from here and proceed with installation.
Make sure to restart R before proceeding.
Then, you can install the development version of CBN2Path by running
the following in R:
Linux and Mac
remotes::install_github("rockwillck/CBN2Path", build_vignettes = TRUE)Windows
remotes::install_github("rockwillck/CBN2Path", build_vignettes = FALSE)Windows support for CBN2Path is limited. Functions will be missing
key functionality; the CBN models developed at ETH-Zurich that
CBN2Path is based on don’t support Windows inherently.
To learn how to use different CBN models and their associated pathway
analysis and visualization functions in the CBN2Path R package, please
run:
vignette("CBN2Path")If you use the CBN2Path package, please cite the paper formally as follows:
Choi-Kim W and Hosseini SR. CBN2Path: an R/Bioconductor package for the analysis of cancer progression pathways using Conjunctive Bayesian Networks. F1000Research 2025, 14:834 (https://doi.org/10.12688/f1000research.168810.1).
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