BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-expression Analysis
Biochemistry, Genetics and Molecular BiologyJilin University and University of missouri columbiaDesign and realize the package
Juexin WangUniversity of Missouri ColumbiaTest the package and review the documents
Yuexu JiangJilin University and University of missouri columbiaTest the package and review the documents.
Description of this data
BFDCA is a comprehensive tool of using Bayes factor for Differential Co-expression (DC) analysis. This package contains three main functions:
(1) clustering condition-specific genes into functional DC subunits;
(2) quantitatively characterizing the regulatory impact of genes based on their differential connectivity within DC structures;
(3) providing a DC-based prediction model to predict case/control phenotypes by taking DC significant gene pairs as markers.
Experiment data files
Steps to reproduce
Users could read the BFDCAVignette.html for quick start of this R package. More details about BFDCA are in the BFDCA-manual.pdf.
This data is associated with the following publication:
Cite this dataset
Wang, Duolin; Wang, Juexin; Jiang, Yuexu (2016), “BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-expression Analysis”, Mendeley Data, v1 http://dx.doi.org/10.17632/jdz4vtvnm3.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.