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data_processing.R

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+# Menu : Microarray #########################################################
+
+## Sub Menu : Atlas ####
+### アトラスを読み込む ####
+SRscore_microarray <- readRDS("data/microarray/SRscore_microarray.rds")
+colnames_microarray <- gsub("\\..+", "", list.files("data/microarray/SRratio/"))
+SRscore_microarray[colnames_microarray] <- round(SRscore_microarray[colnames_microarray])
+
+### アトラスをヒートマップ化する時の色の設定 ####
+paletteLength <- 100
+microarrayBreaks <- c(seq(min(SRscore_microarray[colnames_microarray]), 0, length.out = (paletteLength/2)), 
+              seq(0, max(SRscore_microarray[colnames_microarray]), length.out = (paletteLength/2))[-1])
+microarrayColor <- colorRampPalette(c("deepskyblue", "white", "hotpink"))(paletteLength)
+
+### 外部DBへのリンクをアトラスに追加する ####
+# リンクの見た目設定
+link <- rep("link", nrow(SRscore_microarray))
+
+# AlphaFold2
+url <- rep(paste0("https://alphafold.ebi.ac.uk/search/text/",
+                  SRscore_microarray$ensembl_gene_id))
+AF2 <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# ATTED-II
+url <- rep(paste0("https://atted.jp/kwsearch/?stype=any&kword=", 
+                  SRscore_microarray$ensembl_gene_id, 
+                  "&searchBtnK.x=0&searchBtnK.y=0"))
+ATTED2 <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# eFP Browser
+url <- rep(paste0("https://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi?dataSource=Abiotic_Stress&mode=Absolute&primaryGene=",
+                  SRscore_microarray$ensembl_gene_id))
+eFP <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# KEGG
+url <- rep(paste0("https://www.genome.jp/dbget-bin/www_bget?ath:", SRscore_microarray$ensembl_gene_id))
+KEGG <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# STRING
+url <- rep(paste0("https://string-db.org/cgi/network?identifiers=",
+                  SRscore_microarray$ensembl_gene_id,
+                  "&species=3702&show_query_node_labels=1"))
+STRING <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# TAIR
+url <- rep(paste0("https://www-arabidopsis-org.translate.goog/servlets/TairObject?type=locus&name=", 
+                  SRscore_microarray$ensembl_gene_id, 
+                  "&_x_tr_sl=en&_x_tr_tl=ja&_x_tr_hl=ja&_x_tr_pto=sc"))
+TAIR <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# ThaleMine
+url <- rep(paste0("https://bar.utoronto.ca/thalemine/keywordSearchResults.do?searchTerm=",
+                  SRscore_microarray$ensembl_gene_id, "&searchSubmit=GO"))
+TM <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# それぞれのリンクをアトラスに結合 
+SRscore_microarray <- cbind(SRscore_microarray, "AlphaFold2" = AF2, "ATTED-II" = ATTED2, "eFP Browser" = eFP, 
+                         "KEGG" = KEGG, "STRING" = STRING, "TAIR" = TAIR, "Thale Mine" = TM)
+
+### SRratioの読み込み ####
+ABA_ratiom <- readRDS("data/microarray/SRratio/ABA.rds")
+Cold_ratiom <- readRDS("data/microarray/SRratio/Cold.rds")
+DC3000_ratiom <- readRDS("data/microarray/SRratio/DC3000.rds")
+Drought_ratiom <- readRDS("data/microarray/SRratio/Drought.rds")
+Heat_ratiom <- readRDS("data/microarray/SRratio/Heat.rds")
+`High-light_ratiom` <- readRDS("data/microarray/SRratio/High-light.rds")
+Hypoxia_ratiom2 <- readRDS("data/microarray/SRratio/Hypoxia.rds")
+Osmotic_ratiom <- readRDS("data/microarray/SRratio/Osmotic.rds")
+Oxidation_ratiom <- readRDS("data/microarray/SRratio/Oxidation.rds")
+Salt_ratiom <- readRDS("data/microarray/SRratio/Salt.rds")
+Wound_ratiom <- readRDS("data/microarray/SRratio/Wound.rds")
+
+### メタデータの読み込み ####
+ABA_metadatam <- readRDS("data/microarray/Metadata/ABA.rds")
+Cold_metadatam <- readRDS("data/microarray/Metadata/Cold.rds")
+DC3000_metadatam <- readRDS("data/microarray/Metadata/DC3000.rds")
+Drought_metadatam <- readRDS("data/microarray/Metadata/Drought.rds")
+Heat_metadatam <- readRDS("data/microarray/Metadata/Heat.rds")
+`High-light_metadatam` <- readRDS("data/microarray/Metadata/High-light.rds")
+Hypoxia_metadatam <- readRDS("data/microarray/Metadata/Hypoxia.rds")
+Osmotic_metadatam <- readRDS("data/microarray/Metadata/Osmotic.rds")
+Oxidation_metadatam <- readRDS("data/microarray/Metadata/Oxidation.rds")
+Salt_metadatam <- readRDS("data/microarray/Metadata/Salt.rds")
+Wound_metadatam <- readRDS("data/microarray/Metadata/Wound.rds")
+
+## Sub Menu : Template Matching ####
+### アトラスをgenefinder()に入力可能な形式に変換 ####
+genefinder_microarray <- column_to_rownames(SRscore_microarray, var = "ensembl_gene_id")
+genefinder_microarray <- genefinder_microarray[colnames_microarray]
+genefinder_microarray <- as.matrix(genefinder_microarray)
+
+# GMTファイルを読み込む
+positiveSRscore_ma <- read.gmt("positiveSRscore_ma.gmt")
+negativeSRscore_ma <- read.gmt("negativeSRscore_ma.gmt")
+genesets <- read.gmt("Ara_kegg_go.gmt")
+
+positiveSRscore_ma <- rbind(positiveSRscore_ma, genesets)
+negativeSRscore_ma <- rbind(negativeSRscore_ma, genesets)
+
+# データ集計
+list_microarray <- list(ABA_metadatam, 
+                        Cold_metadatam,
+                        DC3000_metadatam,
+                        Drought_metadatam,
+                        Heat_metadatam,
+                        `High-light_metadatam`,
+                        Hypoxia_metadatam,
+                        Osmotic_metadatam,
+                        Oxidation_metadatam,
+                        Salt_metadatam,
+                        Wound_metadatam
+)
+## 対象サンプルの集計
+numof_control_ma <- list_microarray %>%
+  lapply("[[", "control_sample") %>%
+  lapply(na.omit) %>%
+  lapply(length)
+numof_control_ma <- unlist(numof_control_ma)
+## 実験サンプルの集計
+numof_treatment_ma <- list_microarray %>%
+  lapply("[[", "treated_sample") %>%
+  lapply(na.omit) %>%
+  lapply(length)
+numof_treatment_ma <- unlist(numof_treatment_ma)
+## 研究プロジェクトの集計
+numof_series_ma <- list_microarray %>%
+  lapply("[[", "Series") %>%
+  lapply(unique) %>%
+  lapply(length)
+numof_series_ma <- unlist(numof_series_ma)
+## 集計カテゴリ行とストレス列からなるデータフレームを作成する
+collections_ma <- rbind(numof_control_ma, numof_treatment_ma, numof_series_ma)
+collections_ma <- as.data.frame(collections_ma)
+colnames(collections_ma) <- colnames_microarray
+
+# RNA-Seq #########################################################
+
+## Atlas ####
+### アトラスを読み込む ####
+ABA_metadatam <- readRDS("data/rnaseq/SRscore_rnaseq.rds")
+colnames_rnaseq <- gsub("\\..+", "", list.files("data/rnaseq/SRratio/"))
+SRscore_rnaseq[colnames_rnaseq] <- round(SRscore_rnaseq[colnames_rnaseq])
+
+### アトラスをヒートマップ化する時の色の設定 ####
+paletteLength <- 100
+rnaseqBreaks <- c(seq(min(SRscore_rnaseq[colnames_rnaseq]), 0, length.out = (paletteLength/2)), 
+                  seq(0, max(SRscore_rnaseq[colnames_rnaseq]), length.out = (paletteLength/2))[-1])
+rnaseqColor <- colorRampPalette(c("deepskyblue", "white", "hotpink"))(paletteLength)
+
+### 外部DBへのリンクをアトラスに追加する ####
+# リンクの見た目設定
+link <- rep("link", nrow(SRscore_rnaseq))
+
+# AlphaFold2
+url <- rep(paste0("https://alphafold.ebi.ac.uk/search/text/",
+                  SRscore_rnaseq$ensembl_gene_id))
+AF2 <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# ATTED-II
+url <- rep(paste0("https://atted.jp/kwsearch/?stype=any&kword=", 
+                  SRscore_rnaseq$ensembl_gene_id, 
+                  "&searchBtnK.x=0&searchBtnK.y=0"))
+ATTED2 <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# eFP Browser
+url <- rep(paste0("https://bar.utoronto.ca/efp/cgi-bin/efpWeb.cgi?dataSource=Abiotic_Stress&mode=Absolute&primaryGene=",
+                  SRscore_rnaseq$ensembl_gene_id))
+eFP <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# KEGG
+url <- rep(paste0("https://www.genome.jp/dbget-bin/www_bget?ath:", SRscore_rnaseq$ensembl_gene_id))
+KEGG <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# STRING
+url <- rep(paste0("https://string-db.org/cgi/network?identifiers=",
+                  SRscore_rnaseq$ensembl_gene_id,
+                  "&species=3702&show_query_node_labels=1"))
+STRING <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# TAIR
+url <- rep(paste0("https://www-arabidopsis-org.translate.goog/servlets/TairObject?type=locus&name=", 
+                  SRscore_rnaseq$ensembl_gene_id, 
+                  "&_x_tr_sl=en&_x_tr_tl=ja&_x_tr_hl=ja&_x_tr_pto=sc"))
+TAIR <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# ThaleMine
+url <- rep(paste0("https://bar.utoronto.ca/thalemine/keywordSearchResults.do?searchTerm=",
+                  SRscore_rnaseq$ensembl_gene_id, "&searchSubmit=GO"))
+TM <- paste0("<a href = ", "'", url, "'", ">", link, "</a>")
+
+# 各リンクをアトラスへ結合 
+SRscore_rnaseq <- cbind(SRscore_rnaseq, "AlphaFold2" = AF2, "ATTED-II" = ATTED2, "eFP Browser" = eFP,
+                     "KEGG" = KEGG, "STRING" = STRING, "TAIR" = TAIR, "Thale Mine" = TM)
+
+### SRratioの読み込み ####
+ABA_ratior <- readRDS("data/rnaseq/SRratio/ABA.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Cold.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/DC3000.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Drought.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Heat.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/High-light.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Hypoxia.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Osmotic.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Oxidation.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Salt.rds")
+ABA_ratior <- readRDS("data/rnaseq/SRratio/Wound.rds")
+
+### メタデータの読み込み ####
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/ABA.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Cold.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/DC3000.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Drought.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Heat.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/High-light.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Hypoxia.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Osmotic.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Oxidation.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Salt.rds")
+ABA_metadatar <- readRDS("data/rnaseq/Metadata/Wound.rds")
+
+## Sub Menu : Template Matching ####
+### アトラスをgenefinder()に入力可能な形式に変換 ####
+genefinder_rnaseq <- column_to_rownames(SRscore_rnaseq, var = "ensembl_gene_id")
+genefinder_rnaseq <- genefinder_rnaseq[colnames_rnaseq]
+genefinder_rnaseq <- as.matrix(genefinder_rnaseq)
+
+# GMTファイルを読み込む
+positiveSRscore_rs <- read.gmt("positiveSRscore_rs.gmt")
+negativeSRscore_rs <- read.gmt("negativeSRscore_rs.gmt")
+genesets <- read.gmt("Ara_kegg_go.gmt")
+
+positiveSRscore_rs <- rbind(positiveSRscore_rs, genesets)
+negativeSRscore_rs <- rbind(negativeSRscore_rs, genesets)
+
+# データ集計
+list_rnaseq <- list(ABA_metadatar, 
+                    Cold_metadatar,
+                    DC3000_metadatar,
+                    Drought_metadatar,
+                    Heat_metadatar,
+                    `High-light_metadatar`,
+                    Hypoxia_metadatar,
+                    Osmotic_metadatar,
+                    Oxidation_metadatar,
+                    Salt_metadatar,
+                    Wound_metadatar
+)
+## 対象サンプルの集計
+numof_control_rs <- list_rnaseq %>%
+  lapply("[[", "control_sample") %>%
+  lapply(na.omit) %>%
+  lapply(length)
+numof_control_rs <- unlist(numof_control_rs)
+## 実験サンプルの集計
+numof_treatment_rs <- list_rnaseq %>%
+  lapply("[[", "treated_sample") %>%
+  lapply(na.omit) %>%
+  lapply(length)
+numof_treatment_rs <- unlist(numof_treatment_rs)
+## 研究プロジェクトの集計
+numof_series_rs <- list_rnaseq %>%
+  lapply("[[", "Series") %>%
+  lapply(unique) %>%
+  lapply(length)
+numof_series_rs <- unlist(numof_series_rs)
+## 集計カテゴリ行とストレス列からなるデータフレームを作成する
+collections_rs <- rbind(numof_control_rs, numof_treatment_rs, numof_series_rs)
+collections_rs <- as.data.frame(collections_rs)
+colnames(collections_rs) <- colnames_rnaseq
+
+CollectionsInfo <- function(stress) {
+  HTML(paste0(
+    "<h4> # of control samples : ", stress[1],
+    "<br><br>",
+    "# of treatment samples : ", stress[2],
+    "<br><br>",
+    "# of GSE : ", stress[3],
+    "<br></h3>"
+  ))
+}
+
+# GMTファイルを読み込む
+positiveSRscore_ma <- read.gmt("positiveSRscore_ma.gmt")
+negativeSRscore_ma <- read.gmt("negativeSRscore_ma.gmt")
+
+positiveSRscore_rs <- read.gmt("positiveSRscore_rs.gmt")
+negativeSRscore_rs <- read.gmt("negativeSRscore_rs.gmt")
+
+genesets <- read.gmt("Ara_kegg_go.gmt")
+
+positiveSRscore_ma <- rbind(positiveSRscore_ma, genesets)
+negativeSRscore_ma <- rbind(negativeSRscore_ma, genesets)
+
+positiveSRscore_rs <- rbind(positiveSRscore_rs, genesets)
+negativeSRscore_rs <- rbind(negativeSRscore_rs, genesets)

global.R

@@ -0,0 +1,570 @@
+# Installation
+library("shiny")
+library("shinydashboard")
+library("shinyWidgets")
+library("dplyr")
+library("tibble")
+library("ggplot2")
+library("DT")
+library("withr")
+library("targets")
+library("htmlwidgets")
+library("plotly")
+library("heatmaply")
+library("magrittr")
+library("genefilter")
+library("openxlsx")
+library("clusterProfiler")
+
+# Source scripts
+source("proxy.R", local = TRUE)
+source("data_processing.R", local = TRUE)
+
+# Sub Menu : Atlas ####
+## Tab : Overview ####
+overviewUI <- function(id) {
+  ns <- NS(id)
+  tagList(
+    fluidPage(
+      actionButton(ns("clear"), "Clear Selected Rows"),
+      actionButton(ns("reset"), "Reset Table"),
+      actionButton(ns("remove"), "Remove",
+                   style = "color: red"),
+      br(),
+      br(),
+      dataTableOutput(ns("atlas"))
+      ),
+      br(),
+      br(),
+    fluidRow(
+      column(width = 4,
+             box(title = "Bulk Search",
+                 width = 12,
+                 status = "primary",
+                 solidHeader = TRUE,
+                 textAreaInput(ns("text"), h4("Input list of identifiers :"),
+                               width = "400px", height = "300px"
+                 ),
+                 actionButton(ns("submit"), "Submit",
+                              style = "color: white; background-color: #337ab7; border-color: #2e6da4"),
+                 actionButton(ns("example1"), "Example1"),
+                 actionButton(ns("example2"), "Example2"),
+                 br(),
+                 actionButton(ns("selected"), "Entries shown above"))),
+      column(width = 4,
+             box(title = "Bulk Search → Heatmap",
+                 width = 12,
+                 status = "success",
+                 solidHeader = TRUE,
+                 h4("Control paremeters of heatmap"),
+                 selectInput(ns("identifier"),
+                             label = "Choose y axis :",
+                             choices = c("ensembl_gene_id",
+                                         "SYMBOL"),
+                             selected = "ensembl_gene_id"),
+                 numericInput(ns("height"),
+                              label = "height :",
+                              value = 400),
+                 actionButton(ns("heatmap"), "Plot",
+                              style = "color: white; background-color: #337ab7; border-color: #2e6da4"))),
+      column(width = 4,
+             box(title = "Bulk Search → Enrichment analysis",
+                 width = 12, 
+                 status = "warning",
+                 solidHeader = TRUE,
+                 radioButtons(ns("source"), "Include gene sets from AtSRGA :", c("positiveSRscore (SRscore ≧ 1)", "negativeSRscore (SRscore ≦ -1)"), selected = ""),
+                 actionButton(ns("reset2"), "Reset"),
+                 br(),
+                 br(),
+                 actionButton(ns("analysis"), "Analysis",
+                              style = "color: white; background-color: #337ab7; border-color: #2e6da4"),
+                 br(),
+                 selectInput(ns("xaxis"), 
+                             label = "Choose x-axis :",
+                             choices = c("GeneRatio","Count", "pvalue", 
+                                         "p.adjust", "qvalue"),
+                             selected = "GeneRatio"),
+                 numericInput(ns("showCategory"),
+                              label = "Set number of categories to display :",
+                              value = 30),
+                 numericInput(ns("labelFormat"),
+                              label = "Set wrap length :",
+                              value = 100)
+                 )
+             )
+      ),
+    plotOutput(ns("result"))
+    )
+}
+
+overview <- function(input, output, session, srga, cl, Breaks, Color, prop, positive, negative) {
+  ##　Table Display : SRGA (Stress Response Gene Atlas) ####
+  ### Display the atlas as a heatmap ####
+  rv  <- reactiveValues(df = srga)
+  
+  observeEvent(input$reset, {
+    rv$df <- srga
+  })
+  
+  output$atlas <- renderDataTable({
+    datatable(
+      rv$df,
+      filter = "top",
+      selection = "multiple",
+      extensions = c("Buttons", "FixedColumns"),
+      escape = FALSE,
+      rownames = FALSE,
+      options = list(columnDefs = list(list(className = "dt-nowrap", targets = "_all"),
+                                       list(visible = FALSE, targets = NULL)),
+                     scrollX = TRUE, 
+                     fixedColumns = TRUE,
+                     dom = "lrtBip",
+                     buttons = list(
+                       I("colvis"),
+                       list(extend = "collection",
+                            buttons = list(list(extend = "excel", filename = "SRGA")
+                                           ),
+                            text = "Download"))
+      )
+    ) %>%
+      formatStyle(names(srga[cl]), backgroundColor = styleInterval(Breaks, Color))
+  }, server = TRUE)
+  
+  ## Side Bar : Bulk Search → Heatmap ####
+  ### Input string ####
+  #### Lowercase conversion and delimiter splitting（Space or New Line or Tab or commma）####
+  lower_input <- reactive({
+    gsub("\"", "", strsplit(tolower(input$text), " |\n|\t|,")[[1]])
+  })
+  
+  #### Get index of AGI code ####
+  agi_index <- reactive({
+    grepl("at.g.+", lower_input(), ignore.case = T)
+  })
+  
+  #### Delete Version Part of AGI Code（e.g., ATXGXXXX.1, ATXGXXXXX.3） ####
+  key <- reactive({
+    c(gsub("\\..+", "", lower_input()[agi_index()]), lower_input()[!agi_index()])
+  })
+  
+  ### SRGA ####
+  #### Extract AGI code and SYMBOL for each line
+  AGIandSYMBOL <- reactive(apply(srga[c("ensembl_gene_id", "SYMBOL")], 1, paste, collapse = "/"))
+  
+  #### Divide with a slash ####
+  splited_AGIandSYMBOL <- reactive(strsplit(AGIandSYMBOL(), "/"))
+  
+  #### Convert to lowcase ####
+  lowered_AGIandSYMBOL <- reactive(lapply(splited_AGIandSYMBOL(), tolower))
+  
+  #### Get the index of the element that exactly matches the input string ####
+  matched_AGIandSYMBOL <- reactive(lapply(lowered_AGIandSYMBOL(), match, key()[which(key() != "")]))
+  
+  ### Retrieve the row corresponding to the number from SRGA ####
+  observeEvent(input$submit, {
+    rv$df <- srga[which(lapply(matched_AGIandSYMBOL(), any) == TRUE), ]
+  })
+  
+  ### Remove line ####
+  observeEvent(input$remove, {
+    rv$df <- rv$df[-as.numeric(input$atlas_rows_selected), ]
+  })
+  
+  ## clear selected rows by pressing the button ####
+  observeEvent(input$clear, {
+    selectRows(dataTableProxy("atlas"), NULL)
+  })
+  
+  ### Example of input string ####
+  #### First ####
+  observeEvent(input$example1, {
+    name <- paste("ADH1", "DREB1A", "ELIP1", "HSP17.8", "JAZ1", "NCED3", "PP2CA")
+    updateTextAreaInput(session, "text", value = name)
+  })
+  #### Second ####
+  observeEvent(input$example2, {
+    name <- paste("DREB1A", "DREB1B", "DREB1C", "DREB2A", "DREB2B", "GolS1", "GolS2", "GolS3", sep = "\n")
+    updateTextAreaInput(session, "text", value = name)
+  })
+  observeEvent(input$selected, {
+    updateTextAreaInput(session, "text", value = rv$df$ensembl_gene_id[input$atlas_rows_all])
+  })
+  
+  ### Create heatmap ####
+  heatmap_tbl <- reactive(
+    heatmaply(set_rownames(rv$df[cl], value = rv$df[, input$identifier]),
+              height = input$height,
+              grid_gap = 0.2, grid_color = "gray90",
+              scale_fill_gradient_fun = scale_fill_gradient2(
+                low = "deepskyblue",
+                high = "hotpink",
+                midpoint = 0
+              ),
+              Rowv = FALSE,
+              Colv = FALSE,
+              cellnote = set_rownames(rv$df[cl], value = rv$df[, input$identifier]),
+              cellnote_size = 18,
+              cellnote_textposition = "middle center")
+  )
+  
+  ### Display a heatmap inside the modal dialog box ####
+  output$plot <- renderPlotly({
+    heatmap_tbl()
+  })
+  ns <- session$ns
+  observeEvent(input$heatmap, {
+    showModal(modalDialog({
+      plotlyOutput(ns("plot"))},
+      easyClose = TRUE,
+      size = "l",
+      title = "Heatmap"))
+  })
+  
+  ## 指定した範囲内のSRscoreを持つ遺伝子のID抽出
+  query <- reactive({
+    srga$ensembl_gene_id[which(lapply(matched_AGIandSYMBOL(), any) == TRUE)]
+  })
+  
+  ## カスタムデータのoff
+  observeEvent(input$reset2, {
+    updateRadioButtons(session, 
+                       inputId = "source",
+                       choices = c("positiveSRscore (SRscore ≧ 1)",
+                                   "negativeSRscore (SRscore ≦ -1)"),
+                       selected = "")
+  })
+  
+  observeEvent(input$analysis, {
+    withProgress(message = "", {
+      if (is.null(input$source)) {
+        rv$earesult <- enrichGO(gene = query(),
+                                OrgDb = "org.At.tair.db",
+                                keyType = "TAIR",
+                                ont = "BP",
+                                pvalueCutoff = 0.05,
+                                maxGSSize = 2000)
+      } else if (input$source == "positiveSRscore (SRscore ≧ 1)") {
+        rv$earesult <- enricher(gene = query(),
+                                TERM2GENE = positive,
+                                pvalueCutoff = 0.05,
+                                maxGSSize = 2000)
+      } else if (input$source == "negativeSRscore (SRscore ≦ -1)") {
+        rv$earesult <- enricher(gene = query(),
+                                TERM2GENE = negative,
+                                pvalueCutoff = 0.05,
+                                maxGSSize = 2000)
+      }
+      for (i in 1:10) {
+        incProgress(1/10)
+        Sys.sleep(0.1)
+      }
+    })
+  })
+  
+  output$result <- renderPlot({
+    dotplot(rv$earesult,
+            showCategory = input$showCategory,
+            label_format = input$labelFormat, 
+            x = input$xaxis)
+  })
+  
+  # output$result <- renderDataTable({
+  #   options(digits = 3)
+  #   rv$earesult$p_value <- format(rv$earesult$p_value, scientific = TRUE)
+  #   datatable(
+  #     rv$earesult,
+  #     selection = "single",
+  #     rownames = FALSE,
+  #     extensions = c("Buttons", "FixedColumns"),
+  #     options = list(columnDefs = list(list(className = "dt-nowrap", targets = "_all")),
+  #                    scrollX = TRUE, 
+  #                    dom = 'flrtBip',
+  #                    buttons = list(
+  #                      I("colvis"),
+  #                      list(extend = 'collection',
+  #                           buttons = list(list(extend = 'excel', filename = 'ea_results', exportOptions = list(columns = ":visible"))),
+  #                           text = 'Download'))))
+  # }, server = FALSE)
+  
+  return(list(
+    geneid = reactive(rv$df$ensembl_gene_id[input$atlas_rows_selected]),
+    query_ea = reactive(srga[which(lapply(matched_AGIandSYMBOL(), any) == TRUE), ])
+    )
+    )
+}
+
+## Tab : Abiotic and biotic stress ####
+stressUI <- function(id) {
+  ns <- NS(id)
+  tagList(
+    br(),
+    actionButton(ns("button_ratio"), "Show SRratio", icon("table"),
+                 style = "color: white; background-color: #337ab7; border-color: #2e6da4"),
+    br(),
+    br(),
+    dataTableOutput(ns("ratio")),
+    br(),
+    br(),
+    br(),
+    actionButton(ns("button_metadata"), "Show metadata", icon("table"),
+                 style = "color: white; background-color: #337ab7; border-color: #2e6da4"),
+    actionButton(ns("button_metadata_more"), "", icon("filter"),
+                 style = "color: pink; background-color: white; border-color: #2e6da4"),
+    actionButton(ns("button_metadata_middle"), "", icon("filter"),
+                 style = "color: black; background-color: white; border-color: #2e6da4"),
+    actionButton(ns("button_metadata_less"), "", icon("filter"),
+                 style = "color: skyblue; background-color: white; border-color: #2e6da4"),
+    br(),
+    dataTableOutput(ns("metadata"))
+    )
+}
+
+stress <- function(input, output, session, ratio, srga, selectedRow, metadata) {
+  ## Table Display : SRratio ####
+  rv <- reactiveValues(ratio = NULL, metadata = NULL)
+  
+  ### Retrieve the SR ratio of the specified gene ####
+  selectedRatio <- reactive({
+    ratio[which(ratio$ensembl_gene_id %in% selectedRow()), ]
+  })
+  observeEvent(input$button_ratio, {
+    rv$ratio <- selectedRatio()
+  })
+  
+  ### Display SRratio ####
+  output$ratio <- renderDataTable({
+    num_cl <- which(sapply(rv$ratio, is.numeric))
+    rv$ratio[, num_cl] <- round(rv$ratio[, num_cl], digits = 2)
+    datatable(rv$ratio,
+              extensions = c("Buttons", "FixedColumns"),
+              rownames = FALSE,
+              selection = "single",
+              options = list(scrollX =TRUE,
+                             fixedColumns = TRUE,
+                             dom = 'lrtBip',
+                             buttons = list(list(extend = 'collection',
+                                                 buttons = list(list(extend = 'excel', filename = 'Metadata')),
+                                                 text = 'Download')))) %>%
+      formatStyle(colnames(selectedRatio())[-1], backgroundColor = styleInterval(c(-2, 2), c("skyblue", "white", "pink")))
+  })
+  
+  ### Identify the treated samples that meet the following criteria ####
+  
+  #### Specify a gene in the SRratio table
+  ratio_single <- reactive({
+    rv$ratio[input$ratio_rows_selected, ]
+  })
+  
+  #### SRratio ≧ 2 (1) ####
+  more <- reactive({
+    which(metadata$treated_sample %in% colnames(ratio_single())[ratio_single() >= 2])
+  })
+  
+  #### -2 < SRratio < 2 ####
+  middle <- reactive({
+    which(metadata$treated_sample %in% colnames(ratio_single())[-2 <= ratio_single() & ratio_single() <= 2])
+  })
+  
+  #### SRratio ≦ -2 (2) ####
+  less <- reactive({
+    which(metadata$treated_sample %in% colnames(ratio_single())[ratio_single() <= -2])
+  })
+  
+  ## Table Display : Metadata ####
+  ### Color metadata (1 → pink、2 → skyblue) ####
+  observeEvent(input$button_metadata, {
+    if (length(more()) == 0 & length(less()) == 0) {
+      rv$metadata <- datatable(
+        metadata,
+        selection = "single",
+        rownames = FALSE,
+        options = list(paging = FALSE,
+                       scrollY = "1000px",
+                       columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                       dom = 'flrtBip', 
+                       buttons = list(list(extend = 'collection',
+                                           buttons = list(list(extend = 'excel', filename = 'Metadata')),
+                                           text = 'Download'))))
+    } else {
+    rv$metadata <- datatable(
+      metadata,
+      selection = "single",
+      rownames = FALSE,
+      options = list(paging = FALSE,
+                     scrollY = "1000px",
+                     columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     dom = 'flrtBip', 
+                     buttons = list(list(extend = 'collection',
+                                         buttons = list(list(extend = 'excel', filename = 'Metadata')),
+                                         text = 'Download')))) %>% 
+      formatStyle(
+        "treated_sample", 
+        target = "row",
+        backgroundColor = styleRow(c(more(), less()), c(rep("pink", length(more())), rep("skyblue", length(less())))
+        )
+      )
+  }
+  })
+  
+  ### SRratio ≧ 2のストレス処理サンプルのみを含むメタデータの取得 ####
+  observeEvent(input$button_metadata_more, {
+    rv$metadata <- datatable(
+      metadata[more(), ],
+      selection = "single",
+      rownames = FALSE,
+      options = list(columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     dom = 'flrtBip', 
+                     buttons = list(list(extend = 'collection',
+                                         buttons = list(list(extend = 'excel', filename = 'Metadata_detected_up')),
+                                         text = 'Download')))
+    )
+  })
+  
+  ### -2 < SRratio < 2のストレス処理サンプルのみを含むメタデータの取得 ####
+  observeEvent(input$button_metadata_middle, {
+    rv$metadata <- datatable(
+      metadata[middle(), ],
+      selection = "single",
+      rownames = FALSE,
+      options = list(columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     dom = 'flrtBip', 
+                     buttons = list(list(extend = 'collection',
+                                         buttons = list(list(extend = 'excel', filename = 'Metadata_not_detected')),
+                                         text = 'Download')))
+    )
+  })
+  
+  ### SRratio ≦ -2のストレス処理サンプルのみを含むメタデータの取得 ####
+  observeEvent(input$button_metadata_less, {
+    rv$metadata <- datatable(
+      metadata[less(), ],
+      selection = "single",
+      rownames = FALSE,
+      options = list(columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     dom = 'flrtBip', 
+                     buttons = list(list(extend = 'collection',
+                                         buttons = list(list(extend = 'excel', filename = 'Metadata_detected_down')),
+                                         text = 'Download')))
+    )
+  })
+  
+  ### Display metadata ####
+  output$metadata <- renderDataTable({
+    rv$metadata
+  }, server = FALSE)
+}
+
+# Sub Menu : Template Matching ####
+TemplateMatchUI <- function(id) {
+  ns <- NS(id)
+  
+  tagList(
+    box(title = "Template Matching → Heatmap",
+        width = 4,
+        status = "danger",
+        solidHeader = TRUE,
+        h4("1. Select a gene in overview"),
+        selectInput(ns("method"), 
+                    label = "Choose a method :",
+                    choices = c("euclidean","maximum", "manhattan", 
+                                           "canberra", "correlation", "binary"),
+                    selected = "euclidean"),
+        numericInput(ns("display"),
+                     label = "Number of results to display :",
+                     value = 5),
+        h4("2. Control paremeters of heatmap"),
+        selectInput(ns("identifier"),
+                    label = "Choose y axis :",
+                    choices = c("ensembl_gene_id", "SYMBOL"),
+                    selected = "ensembl_gene_id"),
+        numericInput(ns("height"),
+                     label = "height :",
+                     value = 400),
+        actionButton(ns("heatmap"), "Plot",
+                     style = "color: white; background-color: #337ab7; border-color: #2e6da4")
+        ),
+    dataTableOutput(ns("close_genes")),
+    br(),
+    br(),
+    dataTableOutput(ns("template"))
+    )
+}
+
+TemplateMatch <- function(input, output, session, query, selectRow, srga, cl, Breaks, Color) {
+  ## Table Display : Template Matching results ####
+  ### Template matching ####
+  close_genes <- reactive({
+    genefinder(query,
+               selectRow(),
+               input$display,
+               method = input$method)})
+  
+  ### Display matching result ####
+  output$close_genes <- renderDataTable({
+    datatable(
+      add_column(srga[close_genes()[[1]]$indices, ], 
+                 "dists" = round(close_genes()[[1]]$dists, digits = 3),
+                 .after = max(which(sapply(srga, is.numeric)))
+      ),
+      filter = "top",
+      selection = "single",
+      extensions = c("Buttons", "FixedColumns"),
+      options = list(columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     scrollX = TRUE, fixedColumns = TRUE,
+                     dom = 'lrtBip', buttons = list(list(extend = 'collection',
+                                                          buttons = list(list(extend = 'excel', filename = 'closegenes')),
+                                                          text = 'Download'))
+                     ),
+      escape = FALSE, rownames = FALSE
+      ) %>%
+      formatStyle(names(srga[cl]), backgroundColor = styleInterval(Breaks, Color)) %>%
+      formatStyle("dists", backgroundColor = "yellow")
+  },
+  server = FALSE)
+  
+  ### Display template ####
+  output$template <- renderDataTable({
+    datatable(
+      srga[srga$ensembl_gene_id == selectRow(), ],
+      extensions = "FixedColumns",
+      selection = "single",
+      options = list(columnDefs = list(list(className = 'dt-nowrap', targets = "_all")),
+                     scrollX = TRUE, 
+                     fixedColumns = TRUE,
+                     dom = 'rti'
+                     ),
+      escape = FALSE, rownames = FALSE
+      ) %>%
+      formatStyle(names(srga[cl]), backgroundColor = styleInterval(Breaks, Color))
+  })
+  
+  ## Side Bar : Template Matching → Heatmap ####
+  ### Create heatmap ####
+  heatmap_tbl <- reactive(
+    heatmaply(set_rownames(srga[close_genes()[[1]]$indices, cl], 
+                           value = srga[close_genes()[[1]]$indices, input$identifier]),
+              height = input$height,
+              grid_gap = 0.2, grid_color = "gray90",
+              scale_fill_gradient_fun = scale_fill_gradient2(
+                low = "deepskyblue",
+                high = "hotpink",
+                midpoint = 0
+              ),
+              Rowv = FALSE,
+              Colv = FALSE)
+  )
+  
+  ### Display a heatmap inside the modal dialog box ####
+  output$plot <- renderPlotly({
+    heatmap_tbl()
+  })
+  ns <- session$ns
+  observeEvent(input$heatmap, {
+    showModal(modalDialog({
+      plotlyOutput(ns("plot"))},
+      easyClose = TRUE,
+      size = "l",
+      title = "Heatmap")
+    )
+  })
+}