Package: BICORN 0.1.0

Xi Chen

BICORN: Integrative Inference of De Novo Cis-Regulatory Modules

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.

Authors:Xi Chen [aut, cre], Jianhua Xuan [aut]

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BICORN.pdf |BICORN.html✨
BICORN/json (API)

# Install 'BICORN' in R:
install.packages('BICORN', repos = 'https://cloud.r-project.org')
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.30 score 172 downloads 2 mentions 2 exports 0 dependencies

Last updated 7 years agofrom:acf2011f4a. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-linuxOKMar 31 2025
R-4.4-linuxOKMar 31 2025

Exports:BICORNdata_integration

Dependencies:

An Introduction to BICORN

Xi Chen

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Mar 31 2025.

Last update: 2018-06-06
Started: 2018-06-06

Citation

To cite package ‘BICORN’ in publications use:

Chen X, Xuan J (2018). BICORN: Integrative Inference of De Novo Cis-Regulatory Modules. R package version 0.1.0, https://CRAN.R-project.org/package=BICORN.

Corresponding BibTeX entry: 

  @Manual{,
    title = {BICORN: Integrative Inference of De Novo Cis-Regulatory
      Modules},
    author = {Xi Chen and Jianhua Xuan},
    year = {2018},
    note = {R package version 0.1.0},
    url = {https://CRAN.R-project.org/package=BICORN},
  }