ui.R

library(shiny)
library(plotly)
library(shinythemes)
library(ggplot2)
library(DT)
library(edgeR)
library(pheatmap)
library(threejs)

jscode <- '
$(function() {
var $els = $("[data-proxy-click]");
$.each(
$els,
function(idx, el) {
var $el = $(el);
var $proxy = $("#" + $el.data("proxyClick"));
$el.keydown(function (e) {
if (e.keyCode == 13) {
$proxy.click();
}
});
}
);
});
'

shinyUI(
  navbarPage(
    theme = shinytheme("flatly"),
    a('SingleCellBiology',
      href = 'https://www.jax.org/research-and-faculty/tools/scientific-research-services/genome-tech-single-cell-biology/single-cell-biology',
      target = '_blank'),
    windowTitle = 'Single Cell Biology',
    
    tabPanel(
      'overview',
      fluidRow(div(h3('CellView'), align = 'center')),
      br(),
      fluidRow(div(
        h5(
          'This app is designed for exploratory data analysis of
          processed RNA-Seq data of single cell experiments.'
        ),
        align = 'center'
      )),
      br(),
      br(),
      fluidRow(column(
        5,
        offset = 4,
        fileInput(
          'file1',
          'Choose .Rds file to upload',
          accept = c(
            '.Rds',
            'text/comma-separated-values',
            'text/tab-separated-values',
            'text/plain',
            '.csv',
            '.tsv'
          )
        )
      )),
      
      fluidRow(
      column(5,offset='4',
             htmlOutput('summaryStats'))
      ),
      br(),
      
      fluidRow(column(5, offset = "3",
                      plotlyOutput('tsne_main')))
    ),
    
    navbarMenu(
      'Explore',
      
      tabPanel(
        'Expression',
        
        fluidRow(div(
          p(strong('\tInformation:')),
          tags$ul(
            tags$li(
              strong('Clustering'),
              ':Clustering was performed with t-SNE followed by identification using DBSCAN'
            ),
            tags$li(
              strong('Cluster 0'),
              ':Cells that cannot be assigned to any cluster'
            ),
            tags$li(
              strong('3D Plot'),
              ':Enter gene name to visualize expression in a single cell'
            ),
            tags$li(
              strong('2D Plot'),
              ':Pick a cluster, highlight cells of interest to download gene expression matrix'
            )
          )
        )),
        br(),
        br(),
        fluidRow(
          column(
            2,
            tags$head(tags$script(HTML(jscode))),
            tagAppendAttributes(
              textInput('gene_id', 'Enter gene', value = 'Il6'),
              `data-proxy-click` = "goButton"
            ),
            actionButton('goButton', 'Run')
          ),
          column(2,
                 uiOutput("clusters")),
          column(
            2,
            selectInput(
              'dimension_x',
              label = 'X',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V1'
            )
          ),
          column(
            2,
            selectInput(
              'dimension_y',
              label = 'Y',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V2'
            )
          ),
          column(
            2,
            div(
              align = "center",
              style = "margin-center:50px; margin-top:25px",
              downloadButton("downloadExpression", "Download Expression")
            )
          )
        ),
        br(),
        br(),
        br(),
        fluidRow(
          column(5, offset = 1,
                 plotlyOutput('tsne_plt')),
          column(5, offset = 0,
                 plotOutput('clusterPlot', brush = brushOpts(id =
                                                               'b1')))
        ),
        fluidRow(column(10, offset = 1,
                        plotOutput('gene_vio_plot')))
      ),
      
      tabPanel('Panel plot',
               tags$ul(
                 tags$li(
                   strong('Panel plot'),
                   ':Select a cluster. Enter',
                   strong('ONE'),
                   'or',
                   strong('MULTIPLE'),
                   'gene ids to visualize expression in all clusters'
                 )
                 
               ),
               fluidRow(
                 column(2,
                        uiOutput("clusters4")),
                 column(
                   2,
                   selectInput(
                     'dimension_x4',
                     label = 'X',
                     choice = c('V1', 'V2', 'V3'),
                     selected = 'V1'
                   )
                 ),
                 column(
                   2,
                   selectInput(
                     'dimension_y4',
                     label = 'Y',
                     choice = c('V1', 'V2', 'V3'),
                     selected = 'V2'
                   )
                 ),
                 column(
                   2,
                   tags$head(tags$script(HTML(jscode))),
                   tagAppendAttributes(
                     textInput('panelplotids', 'Comma seperated gene names', value = 'Il6'),
                     `data-proxy-click` = "goButton8"
                   ),
                   actionButton('goButton8', 'Run')
                 )
               ),
               fluidRow(column(
                 10, offset = 1,
                 plotOutput('panelPlot')
               ))
               
      )
    ),
    
    navbarMenu(
      'Co-expression',
      
      tabPanel('AllClusters',
               
               fluidRow(
                 column(
                   2,
                   tags$head(tags$script(HTML(jscode))),
                   tagAppendAttributes(
                     textInput('heatmap_geneids', 'Comma seperated gene names', value = 'Il6,Cd3d,Genes,Umi'),
                     `data-proxy-click` = "goButton1"
                   ),
                   actionButton('goButton1', 'Run')
                 )
               ),
               
               fluidRow(column(
                 10, offset = 1,
                 plotOutput('heatmap')
               ))),
      
      tabPanel(
        'Selected cells',
        tags$ul(
          tags$li(
            strong('Subclustering'),
            ':Select a group of cells in plot1 based based on a single gene expression. Enter multiple gene ids to assess the co-expression of genes in these cells'
          )
          
        ),
        fluidRow(
          column(
            2,
            tags$head(tags$script(HTML(jscode))),
            tagAppendAttributes(
              textInput('gene_id_sch', 'Enter gene', value = 'Il6'),
              `data-proxy-click` = "goButton5"
            ),
            actionButton('goButton5', 'Run')
          ),
          column(2,
                 uiOutput("clusters2")),
          column(
            2,
            selectInput(
              'dimension_x2',
              label = 'X',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V1'
            )
          ),
          column(
            2,
            selectInput(
              'dimension_y2',
              label = 'Y',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V2'
            )
          )
        ),
        fluidRow(column(
          5, offset = 1,
          plotOutput('clusterPlot2', brush = brushOpts(id =
                                                         'scb1'))
        )),
        fluidRow(column(
          2,
          tags$head(tags$script(HTML(jscode))),
          tagAppendAttributes(
            textInput('heatmap_geneids2', 'Comma seperated gene names', value = 'Il6,Cd3d'),
            `data-proxy-click` = "goButton6"
          ),
          actionButton('goButton6', 'Run')
        )),
        fluidRow(column(
          10, offset = 1,
          plotOutput('selectedHeatmap')
        ))
      ),
      
      tabPanel(
        'Binarize',
        tags$ul(
          tags$li(
            strong('Binary Expression'),
            ':Select a cluster. Enter',
            strong('ONE'),
            'or',
            strong('MULTIPLE'),
            'gene ids to assess the co-expression of genes in these cells. Highlighted cells have all genes expressed as determined by a GMM'
          )
          
        ),
        fluidRow(
          column(2,
                 uiOutput("clusters3")),
          column(
            2,
            selectInput(
              'dimension_x3',
              label = 'X',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V1'
            )
          ),
          column(
            2,
            selectInput(
              'dimension_y3',
              label = 'Y',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V2'
            )
          ),
          column(
            2,
            tags$head(tags$script(HTML(jscode))),
            tagAppendAttributes(
              textInput('mclustids', 'Comma seperated gene names', value = 'Il6'),
              `data-proxy-click` = "goButton7"
            ),
            actionButton('goButton7', 'Run')
          )
        ),
        fluidRow(column(
          10, offset = 1,
          plotOutput('plotCoExpression')
        )),
        fluidRow(
          div(
            align = "center",
            style = "margin-center:50px; margin-top:25px",
            downloadButton(
              "downloadExpressionOnOff",
              "Download Expression +ve Cells in cluster"
            )
            
          )
        ),
        br(),
        br(),
        br(),
        fluidRow(
          h4('Positive Cells in all clusters', align = "center"),
          column(6, offset = 3,
                 DT::dataTableOutput('onOffTable'))
        )
      )
    ),
    navbarMenu(
      'Subcluster-analysis',
      tabPanel(
        'DGE Analysis',
        tags$ul(
          tags$li(
            strong('Subclustering'),
            ':Select a group of cells in plot1 and a different group of cells in plot2 for identifying differential features between these subclusters'
          )
          
        ),
        
        fluidRow(
          column(2,
                 uiOutput("clusters1")),
          column(
            2,
            selectInput(
              'dimension_x1',
              label = 'X',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V1'
            )
          ),
          column(
            2,
            selectInput(
              'dimension_y1',
              label = 'Y',
              choice = c('V1', 'V2', 'V3'),
              selected = 'V2'
            )
          ),
          column(2,
                 tags$head(tags$script(HTML(
                   jscode
                 ))),
                 actionButton('goButton2', 'Plot'))
        ),
        
        fluidRow(
          column(4,
                 plotOutput('dge_plot1', brush = brushOpts(id =
                                                             "db1"))),
          column(4,
                 plotOutput('dge_plot2', brush = brushOpts(id =
                                                             'db2'))),
          column(
            2,
            tags$head(tags$script(HTML(jscode))),
            actionButton('goButton3', 'Differential')
          )
        ),
        fluidRow(
          h4('Top Differentially Expressed Genes', offset = 1),
          DT::dataTableOutput('dge')
        ),
        fluidRow(
          div(
            align = "right",
            style = "margin-right:15px; margin-bottom:10px",
            downloadButton("download_dge_table", "Download DGE Table")
          )
          
        )
      )
    )
    
    #  navbarMenu(
    #    'Gene set analysis',
    #    tabPanel(
    #      'KEGG',
    #      tags$ul(
    #        tags$li(
    #          strong('KEGG Pathway'),
    #          ':Select a cluster to investigate significant upregulated KEGG pathways using GAGE'
    #        )
    #      )
    #    ),
    #    tabPanel(
    #      'GO'
    #    )
    #  )
  )
)