The primary novelty of IReNA lies in its ability to decode regulatory relationships among modules using a hypergeometric test. Consequently, if you possess pre-built networks and gene groups, you can directly execute IReNA with the following code. The output of IReNA analysis contains three most important part:

  1. Enriched TFs that regulate other module

  2. Enriched TFs networks: regulatory network of enriched TFs.

  3. Simplified networks: regualtory network among modules.

library(IReNA)
### load test data
load(system.file("extdata", "qucik_start_test.rda", package = "IReNA"))
### Structure of input data. Please note that colnames of your table should be 
### same as the following test data
print(head(grn_test))
##                    TF TFGroup          Target TargetGroup Correlation
## 3370  ENSG00000114315       2 ENSG00000013441           1   0.7201089
## 3404  ENSG00000118263       2 ENSG00000013441           1   0.7146384
## 4323  ENSG00000108055       3 ENSG00000013441           1  -0.7023170
## 10725 ENSG00000025156       1 ENSG00000025156           1   1.0000000
## 18768 ENSG00000064703       1 ENSG00000064703           1   1.0000000
## 21449 ENSG00000066422       1 ENSG00000066422           1   1.0000000
print(head(group_test))
##                 KmeansGroup
## ENSG00000011007           1
## ENSG00000013441           1
## ENSG00000015479           1
## ENSG00000023516           1
## ENSG00000025156           1
## ENSG00000028839           1
### IReNA analysis
IReNA_result <- network_analysis(grn_test,group_test)
## [1] "Total TFs: 227"
## [1] "Enriched TFs: 107"
## [1] "Significant regulations: 6"

Browse enriched TFs that regulate other module

IReNA_result$TF_module_regulation[1:3,]
##                     TF TFGroup           LogFDR TargetGroup RegulationType
## out2   ENSG00000070061       1 3.14614893110143      Group1       Positive
## out2.1 ENSG00000071564       1 2.02272256522902      Group4       Negative
## out2.2 ENSG00000124766       1              Inf      Group4       Negative

Browse enriched TFs network

IReNA_result$TF_network[1:3,]
##                    TF TFGroup TFMinNlogfdr TFMinGroup SigActModules
## 29492 ENSG00000070061       1     3.146149         P1             1
## 31393 ENSG00000182944       3    22.352923         P3             3
## 34854 ENSG00000071564       1     2.022723         N4            NA
##       SigRepModules          Target TargetGroup Correlation Regulation
## 29492            NA ENSG00000070061           1   1.0000000   Positive
## 31393             2 ENSG00000070061           1  -0.7386442   Negative
## 34854             4 ENSG00000071564           1   1.0000000   Positive

Browse simplified networks

IReNA_result$intramodular_network[1:3,]
##                    TFGroup TargetGroup Regulation        Correlation
## Regulation12Pnum         1           1   Positive                  1
## Regulation12Pnum.4       2           2   Positive  0.804181395829719
## Regulation12Nnum.5       2           3   Negative -0.719932554995428
##                    NumberRegulation       Pvalue   NlogFdr
## Regulation12Pnum        9;19;388;19 2.297460e-10  9.270775
## Regulation12Pnum.4  290;306;101;306 6.269939e-56 54.658669
## Regulation12Nnum.5      16;17;17;16 0.000000e+00       Inf