In sigven/oncoEnrichR: Cancer-dedicated gene set interpretation

Tumor co-expression {.tabset}

Using RNA-seq data from ~9,500 primary tumor samples in The Cancer Genome Atlas (TCGA), a co-expression correlation matrix (Pearson rank correlation coefficient) was calculated, indicating pairs of genes that have their expression patterns correlated in tumors
Here, we are showing, across the main primary tumor sites in TCGA:
Tumor suppressor genes, proto-oncogenes or cancer driver genes with a strong/very strong (r >= 0.7 or r <= -0.7 ) correlation to genes in the query set
Here, a maximum of n = 2,500 top associations are shown per correlation direction (a more extensive set, maximum n = 100,000, of top associations are listed in the Excel output of oncoEnrichR)

show_tcga_coexp <- list()
coexp_data <- list()
active_tab <- list()

for(n in c('Positive','Negative')){
  show_tcga_coexp[[n]] <- TRUE
  coexp_data[[n]] <- data.frame()
  active_tab[[n]] <- FALSE

  coexp_data[[n]] <- 
    onc_enrich_report[['data']][['tcga']][['coexpression']] |> 
    dplyr::filter(corrtype == n) |>
    dplyr::select(-corrtype) |>
    head(2500)

  if(n == 'Negative'){
    coexp_data[[n]] <- coexp_data[[n]] |>
      dplyr::arrange(r)
  }

  if(nrow(coexp_data[[n]]) == 0){
    show_tcga_coexp[[n]] <- FALSE
  }
}

if(show_tcga_coexp[['Positive']] == T){
  active_tab[['Positive']] <- T
}else{
  if(show_tcga_coexp[['Negative']] == T){
    active_tab[['Negative']] <- T
  }else{
    active_tab[['Positive']] <- T
  }
}

if(active_tab[['Positive']] == T){
  cat("")
  cat("#### Positive correlation {.active}")
  cat("")
}else{
  cat("")
  cat("#### Positive correlation")
  cat("")
}

coexp_genes_positive <- crosstalk::SharedData$new(coexp_data[['Positive']])

crosstalk::bscols(
  list(
    crosstalk::filter_select("target_gene", "Target gene", 
                             coexp_genes_positive, ~target_gene),
    crosstalk::filter_slider("r", "Correlation coefficient (r)", coexp_genes_positive, 
                             ~r, step = 0.05, min = 0.7, max = 1),
    crosstalk::filter_checkbox("tumor_suppressor", "Tumor suppressor (partner)", 
                               coexp_genes_positive, ~tumor_suppressor)
  ),
  list(
    crosstalk::filter_checkbox("oncogene", "Proto-oncogene (partner)", 
                               coexp_genes_positive, ~oncogene),
    crosstalk::filter_checkbox("cancer_driver", "Cancer driver (partner)", 
                               coexp_genes_positive, ~cancer_driver),
    crosstalk::filter_select("primary_site", "Primary site", 
                             coexp_genes_positive, ~primary_site)

  )
)

htmltools::br()
DT::datatable(coexp_genes_positive, escape = F, 
              extensions=c("Buttons","Responsive"), 
              width = "100%",
              options=list(buttons = c('csv','excel'),dom = 'Bfrtip')
)
rm(coexp_genes_positive)

cat('<br><br>\n <ul><li>  <i> <span style="font-size: 105%; padding: 3px; background-color:#989898; color:white">&nbsp;&nbsp;No genes in the query set with strong positive correlations to tumor suppressors, oncogenes or cancer drivers.&nbsp;&nbsp; </span></i></li></ul>',sep='\n')
cat('\n')
cat('<br><br>')

if(active_tab[['Negative']] == T){
  cat("")
  cat("#### Negative correlation {.active}")
  cat("")
}else{
  cat("")
  cat("#### Negative correlation")
  cat("")
}

coexp_genes_negative <- crosstalk::SharedData$new(coexp_data[['Negative']])

crosstalk::bscols(
  list(
    crosstalk::filter_select("target_gene", "Target gene", 
                             coexp_genes_negative,~target_gene),
    crosstalk::filter_slider("r", "Correlation coefficient (r)", 
                             coexp_genes_negative, 
                              ~r, step = 0.05, min = -1, max = -0.7),
    crosstalk::filter_checkbox("tumor_suppressor", "Tumor suppressor (partner)", 
                               coexp_genes_negative, ~tumor_suppressor)
  ),
  list(
    crosstalk::filter_checkbox("oncogene", "Proto-oncogene (partner)", 
                               coexp_genes_negative, ~oncogene),
    crosstalk::filter_checkbox("cancer_driver", "Cancer driver (partner)", 
                               coexp_genes_negative, ~cancer_driver),
    crosstalk::filter_select("primary_site", "Primary site", 
                             coexp_genes_negative, ~primary_site)
  )
)

htmltools::br()
DT::datatable(coexp_genes_negative, escape = F, 
              extensions=c("Buttons","Responsive"), width = "100%",
              options=list(buttons = c('csv','excel'),dom = 'Bfrtip')
)
rm(coexp_genes_negative)
rm(coexp_data)

cat('<br><br>\n <ul><li>  <i> <span style="font-size: 105%; padding: 3px; background-color:#989898; color:white">&nbsp;&nbsp;No genes in the query set with strong negative correlations to tumor suppressors, oncogenes or cancer drivers.&nbsp;&nbsp; </span></i></li></ul>',sep='\n')
cat('\n')
cat('<br><br>')

{.unlisted .unnumbered .toc-ignore}

Citation Note : If you use the output of the Tumor co-expression module of oncoEnrichR in your research, please cite the following resources and tools: