## ----eval = FALSE------------------------------------------------------------- # library(airway) # data(airway) # se = airway # library(DESeq2) # dds = DESeqDataSet(se, design = ~ dex) # keep = rowSums(counts(dds)) >= 10 # dds = dds[keep, ] # # dds$dex = relevel(dds$dex, ref = "untrt") # # dds = DESeq(dds) # res = results(dds) # res = as.data.frame(res) ## ----eval = FALSE------------------------------------------------------------- # library(InteractiveComplexHeatmap) # library(ComplexHeatmap) # library(circlize) # library(GetoptLong) # # env = new.env() # # make_heatmap = function(fdr = 0.01, base_mean = 0, log2fc = 0) { # l = res$padj <= fdr & res$baseMean >= base_mean & # abs(res$log2FoldChange) >= log2fc; l[is.na(l)] = FALSE # # if(sum(l) == 0) return(NULL) # # m = counts(dds, normalized = TRUE) # m = m[l, ] # # env$row_index = which(l) # # ht = Heatmap(t(scale(t(m))), name = "z-score", # top_annotation = HeatmapAnnotation( # dex = colData(dds)$dex, # sizeFactor = anno_points(colData(dds)$sizeFactor) # ), # show_row_names = FALSE, show_column_names = FALSE, row_km = 2, # column_title = paste0(sum(l), " significant genes with FDR < ", fdr), # show_row_dend = FALSE) + # Heatmap(log10(res$baseMean[l]+1), show_row_names = FALSE, width = unit(5, "mm"), # name = "log10(baseMean+1)", show_column_names = FALSE) + # Heatmap(res$log2FoldChange[l], show_row_names = FALSE, width = unit(5, "mm"), # name = "log2FoldChange", show_column_names = FALSE, # col = colorRamp2(c(-2, 0, 2), c("green", "white", "red"))) # ht = draw(ht, merge_legend = TRUE) # ht # } # # # make the MA-plot with some genes highlighted # make_maplot = function(res, highlight = NULL) { # col = rep("#00000020", nrow(res)) # cex = rep(0.5, nrow(res)) # names(col) = rownames(res) # names(cex) = rownames(res) # if(!is.null(highlight)) { # col[highlight] = "red" # cex[highlight] = 1 # } # x = res$baseMean # y = res$log2FoldChange # y[y > 2] = 2 # y[y < -2] = -2 # col[col == "red" & y < 0] = "darkgreen" # par(mar = c(4, 4, 1, 1)) # # suppressWarnings( # plot(x, y, col = col, # pch = ifelse(res$log2FoldChange > 2 | res$log2FoldChange < -2, 1, 16), # cex = cex, log = "x", # xlab = "baseMean", ylab = "log2 fold change") # ) # } # # # make the volcano plot with some genes highlited # make_volcano = function(res, highlight = NULL) { # col = rep("#00000020", nrow(res)) # cex = rep(0.5, nrow(res)) # names(col) = rownames(res) # names(cex) = rownames(res) # if(!is.null(highlight)) { # col[highlight] = "red" # cex[highlight] = 1 # } # x = res$log2FoldChange # y = -log10(res$padj) # col[col == "red" & x < 0] = "darkgreen" # par(mar = c(4, 4, 1, 1)) # # suppressWarnings( # plot(x, y, col = col, # pch = 16, # cex = cex, # xlab = "log2 fold change", ylab = "-log10(FDR)") # ) # } ## ----eval = FALSE------------------------------------------------------------- # library(shiny) # library(shinydashboard) # body = dashboardBody( # fluidRow( # column(width = 4, # box(title = "Differential heatmap", width = NULL, solidHeader = TRUE, status = "primary", # originalHeatmapOutput("ht", height = 800, containment = TRUE) # ) # ), # column(width = 4, # id = "column2", # box(title = "Sub-heatmap", width = NULL, solidHeader = TRUE, status = "primary", # subHeatmapOutput("ht", title = NULL, containment = TRUE) # ), # box(title = "Output", width = NULL, solidHeader = TRUE, status = "primary", # HeatmapInfoOutput("ht", title = NULL) # ), # box(title = "Note", width = NULL, solidHeader = TRUE, status = "primary", # htmlOutput("note") # ), # ), # column(width = 4, # box(title = "MA-plot", width = NULL, solidHeader = TRUE, status = "primary", # plotOutput("ma_plot") # ), # box(title = "Volcanno plot", width = NULL, solidHeader = TRUE, status = "primary", # plotOutput("volcanno_plot") # ), # box(title = "Result table of the selected genes", width = NULL, solidHeader = TRUE, status = "primary", # DTOutput("res_table") # ) # ), # tags$style(" # .content-wrapper, .right-side { # overflow-x: auto; # } # .content { # min-width:1500px; # } # ") # ) # ) ## ----eval = FALSE------------------------------------------------------------- # library(DT) # library(GetoptLong) # for qq() function # brush_action = function(df, input, output, session) { # # row_index = unique(unlist(df$row_index)) # selected = env$row_index[row_index] # # output[["ma_plot"]] = renderPlot({ # make_maplot(res, selected) # }) # # output[["volcanno_plot"]] = renderPlot({ # make_volcano(res, selected) # }) # # output[["res_table"]] = renderDT( # formatRound(datatable(res[selected, c("baseMean", "log2FoldChange", "padj")], rownames = TRUE), columns = 1:3, digits = 3) # ) # # output[["note"]] = renderUI({ # if(!is.null(df)) { # HTML(qq("

Row indices captured in Output only correspond to the matrix of the differential genes. To get the row indices in the original matrix, you need to perform:

# 
# l = res$padj <= @{input$fdr} &
#     res$baseMean >= @{input$base_mean} &
#     abs(res$log2FoldChange) >= @{input$log2fc}
# l[is.na(l)] = FALSE
# which(l)[row_index]
#
#

where res is the complete data frame from DESeq2 analysis and row_index is the row_index column captured from the code in Output.

")) # } # }) # } ## ----eval = FALSE------------------------------------------------------------- # ui = dashboardPage( # dashboardHeader(title = "DESeq2 results"), # dashboardSidebar( # selectInput("fdr", label = "Cutoff for FDRs:", c("0.001" = 0.001, "0.01" = 0.01, "0.05" = 0.05)), # numericInput("base_mean", label = "Minimal base mean:", value = 0), # numericInput("log2fc", label = "Minimal abs(log2 fold change):", value = 0), # actionButton("filter", label = "Generate heatmap") # ), # body # ) ## ----eval = FALSE------------------------------------------------------------- # server = function(input, output, session) { # observeEvent(input$filter, { # ht = make_heatmap(fdr = as.numeric(input$fdr), base_mean = input$base_mean, log2fc = input$log2fc) # if(!is.null(ht)) { # makeInteractiveComplexHeatmap(input, output, session, ht, "ht", # brush_action = brush_action) # } else { # # The ID for the heatmap plot is encoded as @{heatmap_id}_heatmap, thus, it is ht_heatmap here. # output$ht_heatmap = renderPlot({ # grid.newpage() # grid.text("No row exists after filtering.") # }) # } # }, ignoreNULL = FALSE) # } ## ----eval = FALSE------------------------------------------------------------- # shinyApp(ui, server) ## ----eval = FALSE------------------------------------------------------------- # library(DESeq2) # library(airway) # data(airway) # # dds = DESeqDataSet(airway, design = ~ dex) # dds = DESeq(dds) # # interactivate(dds)