Each target in the query set is annotated with known associations to cancer phenotypes (ontology terms) established from multiple data types through the Open Targets Platform. Annotations are provided both through descriptive associations and rank scores
Indication of putative cancer driver genes require support from at least two of the following sources:
Evidence for genes harboring tumor suppressive or oncogenic functions are provided with three levels of confidence:
Gene function summary is retrieved from NCBI and UniProt Knowledgebase
target_assocs <- onc_enrich_report[['data']][['disease']][['target']] |> dplyr::mutate(targetset_cancer_rank = round( .data$targetset_cancer_rank, digits = 2)) |> dplyr::mutate(global_cancer_rank = round( .data$global_cancer_rank, digits = 2)) |> dplyr::select(-c("tumor_suppressor","oncogene")) |> dplyr::rename(tumor_suppressive = tsg_confidence_level, oncogenic = oncogene_confidence_level) |> dplyr::mutate(tumor_suppressive = dplyr::case_when( tumor_suppressive == "Very strong" ~ "Very strong", tumor_suppressive == "Strong" ~ "Strong", tumor_suppressive == "Moderate" ~ "Moderate", TRUE ~ as.character(tumor_suppressive) )) |> dplyr::mutate(oncogenic = dplyr::case_when( oncogenic == "Very strong" ~ "Very strong", oncogenic == "Strong" ~ "Strong", oncogenic == "Moderate" ~ "Moderate", TRUE ~ as.character(oncogenic) )) |> dplyr::mutate(tumor_suppressive = dplyr::if_else( tumor_suppressive == "None/Limited", "", as.character(tumor_suppressive) )) |> dplyr::mutate(oncogenic = dplyr::if_else( oncogenic == "None/Limited", "", as.character(oncogenic) )) tsg_confidence_levels <- levels(as.factor( target_assocs$tumor_suppressive)) oncogene_confidence_levels <- levels(as.factor( target_assocs$oncogenic)) targets_shared <- crosstalk::SharedData$new(target_assocs) crosstalk::bscols( list( crosstalk::filter_select("symbol", "Target", targets_shared, ~symbol), crosstalk::filter_select("tumor_suppressive", "Tumor suppressor evidence", targets_shared, ~tumor_suppressive), crosstalk::filter_select("oncogenic", "Oncogene evidence", targets_shared, ~oncogenic) ), list( crosstalk::filter_select("cancer_associations", "Associated cancer types", targets_shared, ~cancer_associations), crosstalk::filter_select("disease_associations", "Associated diseases (non-cancer)", targets_shared, ~disease_associations), crosstalk::filter_checkbox("cancer_driver", "Potential cancer driver", targets_shared, ~cancer_driver) ) ) htmltools::br() dt <- DT::datatable( targets_shared, escape = F, extensions=c("Buttons","Responsive"), width = "100%", options=list(buttons = c('csv','excel'), #columnDefs = list(list(className = 'dt-center', targets = 3:5)), pageLength = 20, dom = 'Blfrtip')) |> DT::formatStyle('oncogenic', textAlign = 'center') |> DT::formatStyle('tumor_suppressive', textAlign = 'center') |> DT::formatStyle("symbol", "targetset_cancer_rank", color = "white", backgroundColor = DT::styleInterval( onc_enrich_report[['config']][['disease']][['breaks']], onc_enrich_report[['config']][['disease']][['colors']]) ) if(length(tsg_confidence_levels) > 0){ dt <- dt |> DT::formatStyle( "tumor_suppressive","tumor_suppressive", color = "white", backgroundColor = DT::styleEqual( c("Very strong", "Strong", "Moderate"), c("#5A5A5A", "#898989", "#BBBBBB")) ) } if(length(oncogene_confidence_levels) > 0){ dt <- dt |> DT::formatStyle( "oncogenic", "oncogenic", color = "white", backgroundColor = DT::styleEqual( c("Very strong", "Strong", "Moderate"), c("#5A5A5A", "#898989", "#BBBBBB")) ) } dt
cat('<i>No genes with disease associations from Open Targets Platform were found.</i>',sep='\n') cat('\n')
oe_ttype_matrix <- onc_enrich_report[['data']][['disease']][['ttype_matrix']] if(NROW(oe_ttype_matrix) > 100){ oe_ttype_matrix <- oe_ttype_matrix[1:100,] } if(NROW(oe_ttype_matrix) > 1){ oe_ttype_matrix <- oe_ttype_matrix[nrow(oe_ttype_matrix):1, ] } n_percent_ticks <- 10 if(NROW(oe_ttype_matrix) < 20){ n_percent_ticks <- 5 } target_ttype_rank_fig <- plotly::plot_ly( colors = "Blues", width = 800, height = 400 + (14.67 * NROW(oe_ttype_matrix))) |> #width = 1040, #height = 520 + (19.071 * NROW(oe_ttype_matrix))) |> plotly::add_heatmap( y = rownames(oe_ttype_matrix), x = colnames(oe_ttype_matrix), z = oe_ttype_matrix, hovertext = "Tumor type percent rank", yaxis = "y") |> plotly::layout( title = 'Tumor type association rank', xaxis = list(tickfont = list(size = 13, family = "Helvetica"), tickangle = -50), yaxis = list(tickfont = list(size = 12, family = "Helvetica")), margin = list(l = 75, r = 20, b = 150, t = 30, pad = 4) ) |> plotly::colorbar( nticks = n_percent_ticks, title = list(text = "Percent rank",side = "bottom"), limits = c(0, plyr::round_any(max(oe_ttype_matrix), 100, ceiling))) rm(oe_ttype_matrix) target_ttype_rank_fig
cat('<br>') cat('\n <ul><li> <i> <span style="font-size: 100%; padding: 3px; background-color:#989898; color:white"> <b>NOT SHOWN</b> - limited/few tumor-type specific associations found for genes in the query set. </span></i></li></ul>',sep='\n') cat('\n') cat('<br><br>')
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