Bayesian network feature finder (BANFF)

General Information

Description	An R package for gene network feature selection
Homepage	https://cran.r-project.org/web/packages/BANFF/index.html

Publications

Bioinformatics (2016)

Bayesian network feature finder (BANFF): an R package for gene network feature selection

Zhou Lan; Yize Zhao; Jian Kang; Tianwei Yu

Motivation: Network marker selection on genome-scale networks plays an important role in the understanding of biological mechanisms and disease pathologies. Recently, a Bayesian nonparametric mixture model has been developed and successfully applied for selecting genes and gene sub-networks. Hence, extending this method to a unified approach for network-based feature selection on general large-scale networks and creating an easy-to-use software package is on demand.

Results: We extended the method and developed an R package, the Bayesian network feature finder (BANFF), providing a package of posterior inference, model comparison and graphical illustration of model fitting. The model was extended to a more general form, and a parallel computing algorithm for the Markov chain Monte Carlo -based posterior inference and an expectation maximization-based algorithm for posterior approximation were added. Based on simulation studies, we demonstrate the use of BANFF on analyzing gene expression on a protein–protein interaction network.

Availability: https://cran.r-project.org/web/packages/BANFF/index.html

Contact: jiankang@umich.edu, tianwei.yu@emory.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btw522

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