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iRafNet (version 1.1-1)

Integrative Random Forest for Gene Regulatory Network Inference

Description

Provides a flexible integrative algorithm that allows information from prior data, such as protein protein interactions and gene knock-down, to be jointly considered for gene regulatory network inference.

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Version

Install

install.packages('iRafNet')

Monthly Downloads

104

Version

1.1-1

License

GPL (>= 2)

Maintainer

Francesca Petralia Developer

Last Published

October 26th, 2016

Functions in iRafNet (1.1-1)

roc_curve

Plot receiver operating characteristic (ROC) curve for weighted network generated by iRafNet
iRafNet

Integrative random forest for gene regulatory network inference
iRafNet_network

Compute permutation-based FDR of importance scores and return estimated regulations.
Run_permutation

Derive importance scores for M permuted data sets.
iRafNet_permutation

Derive importance scores for one permuted data.