iRafNet v1.1-1


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Integrative Random Forest for Gene Regulatory Network Inference

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.

Functions in iRafNet

Name Description
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.
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Date 2016-10-26
License GPL (>= 2)
Packaged 2016-10-26 00:46:40 UTC; petraf01
NeedsCompilation yes
Repository CRAN
Date/Publication 2016-10-26 10:37:49

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