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BICORN (version 0.1.0)

Integrative Inference of De Novo Cis-Regulatory Modules

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.

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Version

Install

install.packages('BICORN')

Monthly Downloads

225

Version

0.1.0

License

GPL-2

Maintainer

Xi Chen

Last Published

June 6th, 2018

Functions in BICORN (0.1.0)

TF-gene binding network sampled from the previous round

Transcription Factor Activity Sampling Function

baseline_sampling

Gene Baseline Expression Sampling Function

Inverse-gamma distribution hyper-parameter beta

Genes in the expression data

Transcription factr activity matrix

BICORN Algorithm Function

C_sampling_cluster

cis-Regulatory Module Sampling Function

Gene expression data

sigmanoise_sampling

Fitting Residule Variance Sampling Function

Variance of gene expression fitting residuals.

Regulation Strength Sampling Function

TFs in the prior binding network

Genes in the prior binding network

data_integration

Data Initialization for BICORN

Transcription factr activity matrix sampled from the previous round

Regulation strength variance

TF-gene regulation strength matrix sampled from the previous round

TF-gene regulation strength matrix

Prior TF-gene binding network

TF-gene binding network

Prior TF-gene binding network

Gene baseline expression

Gene baseline expression sampled from the previous round.

Transcription factor activity variance

Gene expression data used for module inference

Variance of baseline gene expression.

Inverse-gamma distribution hyper-parameter alpha