inst/shiny/modules/15-ui-cluster_GSEA.R

In goushixue/QRseq: Quickly RNA-seq Analysis Platform

fluidPage(
  style = "margin-left: 10px; margin-right:10px;",
  box(
    title = "Runing GSEA or ORA:", id = "clp_gsea_tab", width = 12, collapsible = TRUE, solidHeader = TRUE,
    fluidRow(
      column(3,selectInput("clp_gsea_source", "Function Source:",
                           c("Gene Ontology"="GO", "KEGG Pathway"="KEGG", "Reactome Pathway"="Reactome"),width = "100%")),
      column(3, uiOutput('clp_gsea_gsets')),
      conditionalPanel(
        "input.clp_gsea_source=='GO'",
        column(3, selectInput("gsea_GO_ont", "Sub Ontologies:", c("BP", "CC", "MF"),width = "100%"))
      ),
      conditionalPanel(
        "input.clp_gsea_source=='Reactome'",
        column(3, selectInput("gsea_reactome_organism", "Select organism:", c("human", "mouse", "rat", "celegans", "fly", "yeast", "zebrafish"),width = "100%"))
      ),
      column(3, selectInput("clp_gsea_pAdjustMethod", "pAdjustMethod:", width = "100%", c("BH", "holm", "hochberg", "hommel", "bonferroni", "BY", "fdr", "none"))),
      column(3, selectInput("gsea_method", "Performed By:", choices = c("fgsea", "DOSE"), width = "100%")),
      column(3, numericInput("clp_gsea_pval", "Pvalue threshold:", value = 0.05,  min = 0, max = 1, width = "100%")),
      column(3, numericInput("clp_gsea_minGSSize", "minGSSize:", value = 10, width = "100%")),
      conditionalPanel(
        "input.clp_gsea_source=='KEGG'",
        column(3, numericInput("clp_gsea_maxGSSize", "maxGSSize:", value = 1000, width = "100%"))
      ),
      column(3, selectInput("clp_gsea_seed", "seed:", c("TRUE", "FALSE"), width = "100%")),
      column(12, align = 'center', actionButton("start_clp_gsea", "Start ClusterProfiler",
                                                style = "height:40px;font-size:18px", class = "run-button", width = "300px"))
    )
  ),
  conditionalPanel(
    "input.start_clp_gsea",
    tabsetPanel(
      tabPanel(
        "Enrichment Results Visualization",
        style = "padding-top: 5px; padding-left: 0px; padding-right: 0px;margin-left: 0px; margin-right: 0px;",
        box(
          title = "Visualization of Results", width = 4, solidHeader = TRUE,
          radioButtons("gseaPlot_type", "Methods to visualize:", c("dotplot", "gseaplot2", "ridgeplot", "exprs_heatmap"), inline = T, width = "100%" ),
          conditionalPanel(
            "input.gseaPlot_type == 'gseaplot2' | input.gseaPlot_type == 'exprs_heatmap'",
            uiOutput("expr_gseaID"),
          ),
          conditionalPanel(
            "input.gseaPlot_type == 'gseaplot2'",
            # uiOutput("expr_gseaID"),
            selectInput("gsea_ES","Geom for plotting running enrichment score:", choices = c("line", "dot"), width = "100%"),
            # selectizeInput("gsea_color", "color of score line:", choices = colors(), selected = "green", width = "100%"),
            selectInput("gsea_pTable","whether add pvalue table:", choices = c("FALSE", "TRUE"), width = "100%")
          ),
          conditionalPanel(
            "input.gseaPlot_type == 'dotplot' | input.gseaPlot_type == 'ridgeplot'",
            selectInput("gsea_useTop", "Auto or custom choices terms:", c("use topN terms", "custom select terms"), width = "100%"),
            conditionalPanel(
              "input.gsea_useTop == 'use topN terms'",
              numericInput("gsea_nterms", "TopN terms:", value = 10, width = "100%"),
            ),
            conditionalPanel(
              "input.gsea_useTop == 'custom select terms'",
              uiOutput("gseaID")
            ),
            selectInput("gsea_colorBy", "Color plots by:", c("p.adjust", "pvalue", "qvalue"), width = "100%")
          ),
          conditionalPanel(
            "input.gseaPlot_type == 'exprs_heatmap'",
            # uiOutput("expr_gseaID"),
            uiOutput("gsea_exprs_group"),
            selectInput("gsea_data_use", "Values Used To Visualize:", width = "100%",
                        c("rlog or vst transformed value" = "trans_value", "log2(normalized_counts + 1)" = "rel_value",
                          "DESeq2 normalized counts" = "norm_value")),
            # textInput("gsea_heatmap_color", "color:", value = "navy,white,red",  width = "100%"),
            # numericRangeInput("gsea_cluster_break", "Color bar value:", value = c(-2,2), width = "100%")
          ),
          numericInput("gsea_fontsize", "Fontsize:", value = 15,  min = 0, max = 50, width = "100%"),
          # conditionalPanel(
          #   "input.gseaPlot_type == 'exprs_heatmap'",
          #   awesomeCheckbox( inputId = "gsea_cluster_row", label = "Cluster genes:", value = TRUE, status = "info", width = "100%" )
          # ),
          actionButton("gsea_plot_modal_but", "Additional Parameters ...", width = "100%",
                       style = "background-color: rgb(255,255,255);text-align:left;margin-bottom:10px", icon = icon("plus-square")),
          disabled(
            actionButton("PlotGSEA", "Plot gsea", class = "plot-button", width = "100%")
          )
        ),
        bsModal(
          "gsea_plot_modal",  "Additional Parameters", "gsea_plot_modal_but", size = "large",
          fluidPage(
            style = "text-align:justify;color:black;background-color:lavender;border-radius:10px;border:1px solid black;",
            conditionalPanel(
              "input.gseaPlot_type=='dotplot'",
              h2("Additional Parameters of 'dotplot':"), hr(),
              textAreaInput("gsea_dotplot_ggText", "ggplot2 codes:", value = 'theme(axis.title = element_text(size = 21, face = "bold", color = "black", family = "Times"),
                  axis.text = element_text(size = 18, face = "bold", color = "black", family = "Times"),
                  text = element_text(size = 18, face = "bold", color = "black", family = "Times"))', width = "100%", rows = 12)
            ),
            conditionalPanel(
              "input.gseaPlot_type=='gseaplot2'",
              h2("Additional Parameters of 'gseaplot2':"), hr(),
              # textAreaInput("gsea_gseaplot2_ggText", "ggplot2 codes:", value = 'theme(axis.title = element_text(size = 21, face = "bold", color = "black", family = "Times"),
              #     axis.text = element_text(size = 18, face = "bold", color = "black", family = "Times"),
              #     text = element_text(size = 18, face = "bold", color = "black", family = "Times"))', width = "100%", rows = 12)
            ),
            conditionalPanel(
              "input.gseaPlot_type=='ridgeplot'",
              h2("Additional Parameters of 'ridgeplot':"), hr(),
              textAreaInput("gsea_ridgeplot_ggText", "ggplot2 codes:", value = 'theme(axis.title = element_text(size = 21, face = "bold", color = "black", family = "Times"),
                  axis.text = element_text(size = 18, face = "bold", color = "black", family = "Times"),
                  text = element_text(size = 18, face = "bold", color = "black", family = "Times"))', width = "100%", rows = 12)
            ),
            conditionalPanel(
              "input.gseaPlot_type == 'exprs_heatmap'",
              h2("Additional Parameters of 'exprs_heatmap':"), hr(),
              conditionalPanel(
                "input.gsea_heat_colname",
                selectInput("gsea_heat_angle", "Column names angle:", choices = c('0', '45', '90', '270', '315'), selected = '315', width = "100%")
              ),
              numericRangeInput("gsea_cluster_break", "Color bar value:", value = c(-2,2), width = "100%"),
              numericInput("gsea_heatmap_fontsize", "Fontsize:", value = 15, width = "100%")
            )
          )
        ),
        column(
          6,
          wellPanel(
            style = "padding-top:5px",
            fluidRow(
              column(
                12, style = "padding-left:0px;margin-left:0px;padding-right:0px;margin-right:0px;border-bottom:solid 1px rgb(224,224,224)",
                column(
                  6, style = "padding-left:10px;",
                  tags$h4("Enrichment Results Visualization:")
                ),
                column(
                  6, align = "right", style = "padding-top:5px;",
                  dropdownButton(
                    numericInput('gsea_width', 'Figure Width:', min = 1, max = 20, value = 12, width = "100%"),
                    numericInput('gsea_height', 'Figure Height:', min = 1, max = 20, value = 4, width = "100%"),
                    downloadButton('gsea_Pdf','Download .pdf', class = "btn btn-warning", width = "100%"),
                    circle = FALSE, status = "danger", size = "sm", icon = icon("save"), width = "200px",
                    right = TRUE, tooltip = tooltipOptions(title = "Click to download figures !")
                  )
                )
              )
            ),
            uiOutput("gseaPlotUI")
          )
        ),
        column(
          2,
          wellPanel(
            sliderInput("clp_gsea_plot_width", "Figure Width (%):", min = 50, max = 100, value = 100, step = 2, width = "100%"),
            sliderInput("clp_gsea_plot_height", "Figure Height (px):", min = 200, max = 1000, value = 438, step = 2, width = "100%")
          ),
          conditionalPanel(
            "input.gseaPlot_type == 'exprs_heatmap'",
            wellPanel(
              checkboxInput("gsea_heat_rowname", "Showing rownames ?", value = TRUE, width = "100%"),
              checkboxInput("gsea_heat_colname", "Showing colnames ?", value = FALSE, width = "100%")
            )
          )
        )
      ),
      tabPanel(
        "Enrichment Results Table",
        fluidPage(
          style = "padding-top: 5px; padding-left: 0px; padding-right: 0px;margin-left: 0px; margin-right: 0px;",
          withSpinner(dataTableOutput("gsea_Tab")),
          downloadButton('gsea_Tab_Csv','Download .csv', class = "btn", width = "100%")
        )
      )
    )
  ),
  column(
    12,
    fluidRow(
      style = "background-color: rgb(248,249,250); border: 1px solid rgb(218,219,220); padding: 5px; margin:5px; border-radius: 15px;",
      column(
        4, style = "text-align:center;border-right: 2px solid white; padding-top:15px",
        tags$img(src = "images/demo/GSEA_Plot.png",
                 width = "100%")
      ),
      column(
        8, style = "text-align:justify;",
        h3("What is Gene Set Enrichment Analysis (GSEA) ?"),
        p("A common approach to analyzing gene expression profiles is identifying differentially 
          expressed genes that are deemed interesting. The ORA enrichment analysis is based on these 
          differentially expressed genes. This approach will find genes where the difference is large 
          and will fail where the difference is small, but evidenced in coordinated way in a set of related 
          genes. Gene Set Enrichment Analysis (GSEA)(Subramanian et al. 2005) directly addresses this limitation. 
          All genes can be used in GSEA; GSEA aggregates the per gene statistics across genes within a gene set, 
          therefore making it possible to detect situations where all genes in a predefined set change in a small 
          but coordinated way. This is important since it is likely that many relevant phenotypic differences are 
          manifested by small but consistent changes in a set of genes."),
        p("In GSEA analysis, genes are ranked based on their phenotypes. Given apriori defined set of gene S 
          (e.g., genes sharing the same GO category), the goal of GSEA is to determine whether the members of S 
          are randomly distributed throughout the ranked gene list L (e.g., all the genes in your RNA-seq data that
          ranked by log2foldchange of two biological states) or primarily found at the top or bottom.")
      )
    )
  ),
  column(
    12,
    hr(),
    fluidRow(
      style = "margin-bottom:20px",
      column(3, align = "right", actionLink("pGSEA", "<< Previous", style = "font-size: 20px")),
      column(6, align = "center"),
      column(3, align = "left", actionLink("nGSEA", "Next >>", style = "font-size: 20px"))
    )
  )
)