The query set is annotated with data from COMPARTMENTS, a weekly updated database of subcellular localization data for human proteins, and results are here presented in two different views:
A subcellular anatogram - acting as a "heatmap" of subcellular structures associated with proteins in the query set
r onc_enrich_report$config$subcellcomp$minimum_confidence
r onc_enrich_report$config$subcellcomp$minimum_channels
r !onc_enrich_report$config$subcellcomp$show_cytosol
suppressPackageStartupMessages(library(gganatogram)) subcellcomp_geneset_density <- onc_enrich_report[['data']][['subcellcomp']][['anatogram']] if(onc_enrich_report[['config']][['subcellcomp']][['show_cytosol']] == F){ subcellcomp_geneset_density <- subcellcomp_geneset_density |> dplyr::filter(organ != "cytosol") } gganatogram::gganatogram( data = subcellcomp_geneset_density, outline = T, fillOutline = 'lightgray', organism = 'cell', fill = 'value') + ggplot2::theme_void() + ggplot2::coord_fixed() + ggplot2::scale_fill_gradient( low ="#FFEDA0", high = "#800026")
plot_data <- onc_enrich_report[['data']][['subcellcomp']][['anatogram']] |> dplyr::arrange(value) plot_data$organ <- factor(plot_data$organ, levels = plot_data$organ) plot_data$toDownlight <- "NO" if(onc_enrich_report[['config']][['subcellcomp']][['show_cytosol']] == F){ plot_data <- plot_data |> dplyr::mutate(toDownlight = dplyr::if_else( organ == "cytosol", as.character("YES"), as.character(toDownlight) )) } p <- ggplot2::ggplot( plot_data, ggplot2::aes( x = organ, y = value, fill = toDownlight) ) + ggplot2::geom_bar( stat = "identity" ) + ggplot2::ylab("Percent of query gene set") + ggplot2::scale_fill_manual( values = c("YES"="gray", "NO"="BLACK" ), guide = FALSE ) + ggplot2::xlab("") + ggplot2::ylim(0,100) + ggplot2::theme_classic() + ggplot2::coord_flip() + ggplot2::theme( legend.position = "none", axis.text.x = ggplot2::element_text(size = 11, vjust = 0.5), legend.text = ggplot2::element_text(face = "bold", family = "Helvetica", size = 11), axis.text.y = ggplot2::element_text(family = "Helvetica", size = 11), axis.title.x = ggplot2::element_text(family = "Helvetica", size = 11), axis.title.y = ggplot2::element_text(family = "Helvetica", size = 11) ) plotly::ggplotly(p, width = 600, height = 600)
subcell_comp_all <- crosstalk::SharedData$new(onc_enrich_report[['data']][['subcellcomp']][['all']]) crosstalk::bscols( list( crosstalk::filter_select("target_gene", "Target gene", subcell_comp_all,~symbol), crosstalk::filter_select("supporting_channels", "Supporting channels", subcell_comp_all, ~supporting_channels) ), list( crosstalk::filter_select("supporting_sources", "Supporting sources", subcell_comp_all, ~supporting_sources), crosstalk::filter_slider("minimum_confidence", "Minimum confidence level (across channels)", subcell_comp_all, ~minimum_confidence, step = 1, min = 3, max = 5) ) ) htmltools::br() DT::datatable(subcell_comp_all, escape = F, extensions=c("Buttons","Responsive"), width = "100%", options=list(buttons = c('csv','excel'),dom = 'Bfrtip') )
r onc_enrich_report$config$subcellcomp$minimum_confidence
htmltools::br() DT::datatable(onc_enrich_report[['data']][['subcellcomp']][['grouped']], escape = F, extensions=c("Buttons","Responsive"), width = "100%", options=list(buttons = c('csv','excel'),dom = 'Bfrtip'))
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