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BICORN
View on CRAN: Click
here
Download and install BICORN package within the R console
Install from CRAN:
install.packages("BICORN")
Install from Github:
library("remotes")
install_github("cran/BICORN") Install by package version:
library("remotes")
install_version("BICORN", "0.1.0") Attach the package and use:
library("BICORN")
Maintained by
Xi Chen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-06-06
Latest Update: 2018-06-06
Description:
Prior transcription factor binding knowledge and target gene expression data are integrated in a Bayesian framework for functional cis-regulatory module inference. Using Gibbs sampling, we iteratively estimate transcription factor associations for each gene, regulation strength for each binding event and the hidden activity for each transcription factor.
How to cite:
Xi Chen (2018). BICORN: Integrative Inference of De Novo Cis-Regulatory Modules. R package version 0.1.0, https://cran.r-project.org/web/packages/BICORN. Accessed 26 Aug. 2026.
Previous versions and publish date:
No previous versions
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imports, suggests or enhances
Complete documentation for BICORN
Functions, R codes and Examples using
the BICORN R package
Some associated functions: A . A_old . A_sampling . BICORN . Binding_TFs . Binding_genes . Binding_matrix . C . C_old . C_prior . C_sampling_cluster . Exp_data . Exp_genes . X . X_old . X_sampling . Y . alpha . base_line . base_line_old . baseline_sampling . beta . data_integration . sigma_A . sigma_X . sigma_baseline . sigma_noise . sigmanoise_sampling .
Some associated R codes: A_sampling.R . BICORN.function.R . C_sampling_cluster.R . X_sampling.R . baseline_sampling.R . data.initialization.R . sigmanoise_sampling.R . Full BICORN package functions and examples
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