multiDEGGs

Differentially Expressed Gene-Gene pairs in multi omic data

multiDEGGs

The multiDEGGs package test for differential gene-gene correlations across different groups of samples in multi omic data.
Specific gene-gene interactions can be explored and gene-gene pair regression plots can be interactively shown.

Installation

Install from CRAN:
install.packages("multiDEGGs")

Install from Github:
devtools::install_github("elisabettasciacca/multiDEGGs")

Example

Load package and sample data

library(multiDEGGs)  
data("synthetic_metadata")  
data("synthetic_rnaseqData")  
data("synthetic_proteomicData")
data("synthetic_OlinkData")   

Generate differential networks:

assayData_list <- list("RNAseq" = synthetic_rnaseqData,
                       "Proteomics" = synthetic_proteomicData,
                       "Olink" = synthetic_OlinkData)

deggs_object <- get_diffNetworks(assayData = assayData_list,
                                 metadata = synthetic_metadata,
                                 category_variable = "response",
                                 regression_method = "lm",
                                 padj_method = "bonferroni",
                                 verbose = FALSE,
                                 show_progressBar = FALSE,
                                 cores = 2)

Visualise interactively (will open a shiny interface)

View_diffNetworks(deggs_object)

Get a table listing all the significant interactions found in each category

get_multiOmics_diffNetworks(deggs_object, sig_threshold = 0.05)

Plot differential regression fits for a single interaction
plot_regressions(deggs_object, assayDataName = "RNAseq", gene_A = "MTOR", gene_B = "AKT2", legend_position = "bottomright")

Citation

citation("multiDEGGs")