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multiDEGGs

Differentially Expressed Gene-Gene pairs in multi omic data

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")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.