From 6c5b9379f9b4a5ffc271f09665413397400643fb Mon Sep 17 00:00:00 2001
From: Danni Luo <danni.luo@utsouthwestern.edu>
Date: Wed, 2 May 2018 22:40:36 -0500
Subject: [PATCH] update shiny code in vizapp

---
 vizapp/server.R              |  68 +++----
 vizapp/tools/altsplice.R     | 307 ++++++++++++++++++++++++------
 vizapp/tools/altsplice_ui.R  |  56 +++---
 vizapp/tools/dea.R           | 356 +++++++++++++++++++++++++++--------
 vizapp/tools/dea_ui.R        | 122 ++++++------
 vizapp/tools/gc.R            | 263 ++++++++++++++++++++++----
 vizapp/tools/gc_ui.R         |  55 +++---
 vizapp/tools/gsea.R          | 129 +++++++++----
 vizapp/tools/gsea_ui.R       |  48 ++---
 vizapp/tools/intro.R         |  47 +++--
 vizapp/tools/intro_ui.R      | 120 ++++++++++++
 vizapp/tools/qc.R            | 213 ++++++++++++++++++---
 vizapp/tools/qc_ui.R         |  82 ++++----
 vizapp/ui.R                  |  50 +++--
 vizapp/www/bootstrap.min.css |  13 ++
 vizapp/www/style.css         | 169 ++++++++++++++++-
 16 files changed, 1640 insertions(+), 458 deletions(-)
 create mode 100644 vizapp/tools/intro_ui.R
 create mode 100644 vizapp/www/bootstrap.min.css

diff --git a/vizapp/server.R b/vizapp/server.R
index a37441d..10aeef5 100644
--- a/vizapp/server.R
+++ b/vizapp/server.R
@@ -1,33 +1,35 @@
-library(shiny)
-library(Vennerable)
-library(qusage)
-library(DT)
-library(ggplot2)
-library(ballgown)
-library(sqldf)
-library(reshape2)
-library("gplots")
-
-shinyServer(function(input, output, session) {
-
-    data.dir <- Sys.getenv('outputDir')
-    rda.dir <- data.dir
-    symsyn <- read.table(file='symbol2synonym.txt',header=FALSE)
-    names(symsyn) <- c('symbol','synonyms')
-    source('functions.R', local = TRUE)
-    source('tools/intro.R', local = TRUE)
-    source('tools/gc.R', local = TRUE)
-    source('tools/qc.R', local = TRUE)
-    source('tools/altsplice.R', local = TRUE)
-    source('tools/dea.R', local = TRUE)
-    source('tools/gsea.R', local = TRUE)
-    #source('tools/fastqc.R', local = TRUE)
-    source('tools/gc_ui.R', local = TRUE)
-    source('tools/qc_ui.R', local = TRUE)
-    source('tools/dea_ui.R', local = TRUE)
-    source('tools/gsea_ui.R', local = TRUE)
-    #source('tools/fastqc_ui.R', local = TRUE)
-    source('tools/altsplice_ui.R', local = TRUE)
-
-})
-
+library(shiny)
+library(Vennerable)
+library(qusage)
+library(DT)
+library(ggplot2)
+library(ballgown)
+library(sqldf)
+library(reshape2)
+library("gplots")
+
+shinyServer(function(input, output, session) {
+
+   # data.dir <- Sys.getenv('outputDir')
+    data.dir <-"workflow_322_output"
+    rda.dir <- data.dir
+    symsyn <- read.table(file='symbol2synonym.txt',header=FALSE)
+    names(symsyn) <- c('symbol','synonyms')
+    source('functions.R', local = TRUE)
+    source('tools/intro.R', local = TRUE)
+    source('tools/intro_ui.R', local = TRUE)
+    source('tools/gc.R', local = TRUE)
+    source('tools/qc.R', local = TRUE)
+    source('tools/altsplice.R', local = TRUE)
+    source('tools/dea.R', local = TRUE)
+    source('tools/gsea.R', local = TRUE)
+    #source('tools/fastqc.R', local = TRUE)
+    source('tools/gc_ui.R', local = TRUE)
+    source('tools/qc_ui.R', local = TRUE)
+    source('tools/dea_ui.R', local = TRUE)
+    source('tools/gsea_ui.R', local = TRUE)
+    #source('tools/fastqc_ui.R', local = TRUE)
+    source('tools/altsplice_ui.R', local = TRUE)
+
+})
+
diff --git a/vizapp/tools/altsplice.R b/vizapp/tools/altsplice.R
index 2aa81c6..3eb2df7 100644
--- a/vizapp/tools/altsplice.R
+++ b/vizapp/tools/altsplice.R
@@ -1,86 +1,285 @@
 
- get.bgdata <- function(var) {
-   rdafile <- paste(data.dir,'bg.rda',sep='/')
-   load(rdafile)
-   genetrx <- indexes(bg)$t2g
-   genetrx$SYMBOL <- geneNames(bg)
-
-   geneid <- as.character(unique(genetrx[genetrx$SYMBOL %in% var$symsearch,]$g_id))
-   if (exists("var$enssearch") && var$enssearch != '') {
-       geneid <- as.character(unique(genetrx$g_id[grep(enssearch,genetrx$g_id)]))
-     }
-   genebg <- subset(bg,paste0("gene_id=='",geneid,"'"))
-   rownames(genetrx) <- transcriptNames(bg)
-   fpkm <- texpr(bg,meas='FPKM')
-   keep <- genetrx[genetrx$g_id == geneid,]$t_id
-   cttbl <- fpkm[keep,]
-   grps <- pData(bg)$group
-   trxnames <-  genetrx[genetrx$g_id == geneid,]
-   dtm <- melt(t(cttbl))
-   names(dtm) <- c('sample','transcript','value')
-   dtm$grps <- rep(grps,length(keep))
-   if (length(keep) < 2) {
-     dtm$transcript <- rep(keep,length(keep))
-   }
-   dtm$grptrx <- paste(dtm$grps,dtm$transcript,sep='.')
-   test <- stattest(gown=genebg, pData=pData(bg), feature='transcript',covariate='group', libadjust=FALSE,getFC=TRUE)
-   if (length(keep) > 1) {
-     agg = collapseTranscripts(gene=geneid, gown=bg, k=var$kct, method='kmeans')
-     test <- stattest(gowntable=agg$tab, pData=pData(bg), feature='transcript_cluster',covariate='group', libadjust=FALSE,getFC=TRUE)
-   }
-   return(list(stattbl=test,gid=geneid,obj=genebg,cttbl=dtm,tname=trxnames))
- }
+
+get.bgdata <- function(var) {
+  rdafile <- paste(data.dir, 'bg.rda', sep = '/')
+  load(rdafile)
+  genetrx <- indexes(bg)$t2g
+  genetrx$SYMBOL <- geneNames(bg)
+  
+  geneid <- as.character(unique(genetrx[genetrx$SYMBOL %in% var$symsearch, ]$g_id))
+  if (exists("var$enssearch") && var$enssearch != '') {
+    geneid <- as.character(unique(genetrx$g_id[grep(enssearch, genetrx$g_id)]))
+  }
+  genebg <- subset(bg, paste0("gene_id=='", geneid, "'"))
+  rownames(genetrx) <- transcriptNames(bg)
+  fpkm <- texpr(bg, meas = 'FPKM')
+  keep <- genetrx[genetrx$g_id == geneid, ]$t_id
+  cttbl <- fpkm[keep, ]
+  grps <- pData(bg)$group
+  trxnames <-  genetrx[genetrx$g_id == geneid, ]
+  dtm <- melt(t(cttbl))
+  names(dtm) <- c('sample', 'transcript', 'value')
+  dtm$grps <- rep(grps, length(keep))
+  if (length(keep) < 2) {
+    dtm$transcript <- rep(keep, length(keep))
+  }
+  dtm$grptrx <- paste(dtm$grps, dtm$transcript, sep = '.')
+  test <-
+    stattest(
+      gown = genebg,
+      pData = pData(bg),
+      feature = 'transcript',
+      covariate = 'group',
+      libadjust = FALSE,
+      getFC = TRUE
+    )
+  if (length(keep) > 1) {
+      agg = collapseTranscripts(
+      gene = geneid,
+      gown = bg,
+      k = var$kct,
+      method = 'kmeans'
+    )
+    test <-
+      stattest(
+        gowntable = agg$tab,
+        pData = pData(bg),
+        feature = 'transcript_cluster',
+        covariate = 'group',
+        libadjust = FALSE,
+        getFC = TRUE
+      )
+  }
+  return(list(
+    stattbl = test,
+    gid = geneid,
+    obj = genebg,
+    cttbl = dtm,
+    tname = trxnames
+  ))
+}
 
 find_sym <- function (sym) {
-if (!(toupper(sym) %in% toupper(symsyn$symbol))) {
-     syns <- symsyn[grep(input$symsearch,symsyn$synonym,ignore.case=TRUE),]$symbol
-     synlist <- paste(as.character(syns),collapse=',')
-   if (length(syns) > 1) {
-     paste("Please Use Official Gene Symbols",synlist,sep=':')
-   }else {"Please Use Official Gene Symbols"}  	 
- }else {NULL}  	 
-}	 
-
-getgeneid <- eventReactive(input$altButton,{
- if (input$symsearch == '' & input$enssearch != '') {
+  if (!(toupper(sym) %in% toupper(symsyn$symbol))) {
+    syns <-
+      symsyn[grep(input$symsearch, symsyn$synonym, ignore.case = TRUE), ]$symbol
+    synlist <- paste(as.character(syns), collapse = ',')
+    if (length(syns) > 1) {
+      paste("Please Use Official Gene Symbols", synlist, sep = ':')
+    } else {
+      "Please Use Official Gene Symbols"
+    }
+  } else {
+    NULL
+  }
+}
+
+getgeneid <- eventReactive(input$altButton, {
+  if (input$symsearch == '' & input$enssearch != '') {
     validate (find_sym(input$symsearch))
-    }   
-get.bgdata(input)
+  }
+  get.bgdata(input)
 })
 
 output$plot.cluster <- renderPlot({
-  par(oma=c(4,4,1,1)) 
+  par(oma = c(0, 0, 0, 0))
   gid <- getgeneid()$gid
   bg <- getgeneid()$obj
   tname <- getgeneid()$tname
   if (nrow(tname) > 1) {
-    plotLatentTranscripts(gene=gid, gown=bg, k=input$kct, method='kmeans', returncluster=FALSE)
+    plotLatentTranscripts(
+      gene = gid,
+      gown = bg,
+      k = input$kct,
+      method = 'kmeans',
+      returncluster = FALSE
+    )
+  }
+}, height = "auto", width = 'auto')
+
+output$dlplotcluster <- renderUI({
+  if (!is.null(getgeneid()$gid) &
+      !is.null(getgeneid()$obj) & !is.null(getgeneid()$tname)) {
+    downloadButton('Downloadpcluster', 'Download PNG')
   }
 })
 
+output$Downloadpcluster <- downloadHandler(
+  file = function() {
+    paste('plotcluster', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 120,
+      res = 120,
+      pointsize = 5
+    )
+    if (is.null(getgeneid()$gid) &
+        is.null(getgeneid()$obj) & is.null(getgeneid()$tname)) {
+      return()
+    }
+    par(oma = c(4, 4, 1, 1))
+    gid <- getgeneid()$gid
+    bg <- getgeneid()$obj
+    tname <- getgeneid()$tname
+    if (nrow(tname) > 1) {
+      plot <-
+        plotLatentTranscripts(
+          gene = gid,
+          gown = bg,
+          k = input$kct,
+          method = 'kmeans',
+          returncluster = FALSE
+        )
+    }
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+
+
 output$gene.stat <- DT::renderDataTable({
   getgeneid()$stattbl
-},escape=FALSE)
+}, escape = FALSE, options = list(dom = 'ft'))
 
 output$trx.name <- DT::renderDataTable({
   getgeneid()$tname
-},escape=FALSE)
+}, escape = FALSE , options = list(dom = 'ft'))
 
+output$downloadTrx <- renderUI({
+  if (!is.null(getgeneid()$tname)) {
+    downloadButton('DownloadTrx', 'Download CSV')
+  }
+})
+output$DownloadTrx <- downloadHandler(
+  file <- paste('Gene.trxname.txt'),
+  content = function(file) {
+    write.table(
+      getgeneid()$tname,
+      file,
+      quote = FALSE,
+      row.names = FALSE,
+      sep = '\t'
+    )
+  }
+)
 
 output$plot.means <- renderPlot({
-  par(oma=c(4,4,1,1))
-  par(cex.main=0.75)
+  par(oma = c(1, 4, 1, 8))
+  par(cex.main = 0.75)
   gid <- getgeneid()$gid
   bg <- getgeneid()$obj
   tname <- getgeneid()$tname
   if (nrow(tname) > 1) {
-    plotMeans(gid, bg, groupvar='group', meas='cov', colorby='transcript')
+    plotMeans(gid,
+              bg,
+              groupvar = 'group',
+              meas = 'cov',
+              colorby = 'transcript')
+  }
+}, height = 900, width = "auto")
+
+output$dlplotmean <- renderUI({
+  if (!is.null(getgeneid()$gid) & !is.null(getgeneid()$obj) & !is.null(getgeneid()$tname)) {
+    downloadButton('Downloadmean', 'Download PNG')
   }
-}, height = 900, width = 900)
+})
+
+output$Downloadmean <- downloadHandler(
+  file = function() {
+    paste('mean', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 180,
+      res = 140,
+      pointsize = 5
+    )
+    if (is.null(getgeneid()$gid) & is.null(getgeneid()$obj) & is.null(getgeneid()$tname)) {
+      return()
+    }
+    countTable <- getgeneid()$cttbl
+    par(oma = c(1, 4, 1, 8))
+    par(cex.main = 0.75)
+    gid <- getgeneid()$gid
+    bg <- getgeneid()$obj
+    tname <- getgeneid()$tname
+    if (nrow(tname) > 1) {
+      plot <- plotMeans(gid,
+                bg,
+                groupvar = 'group',
+                meas = 'cov',
+                colorby = 'transcript')
+    }
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+
+
 
 output$trx.gene <- renderPlot({
   countTable <- getgeneid()$cttbl
-  par(oma=c(4,4,1,1))
-  p <- ggplot(countTable,aes(x=grptrx,y=log2(value+1))) + geom_boxplot(aes(fill = factor(grptrx))) + geom_jitter(height = 0) + theme(legend.position="left",axis.text.x=element_text(angle=45,hjust=1, vjust=1),legend.key.height=unit(0.5,"line"),legend.text=element_text(size=8),legend.title=element_blank()) + ylab("Relative Abundance (FPKM)") + xlab("")
+  par(oma = c(4, 1, 4, 1))
+  p <-
+    ggplot(countTable, aes(x = grptrx, y = log2(value + 1))) + geom_boxplot(aes(fill = factor(grptrx))) + geom_jitter(height = 0) + theme(
+      legend.position = "left",
+      axis.text.x = element_text(
+        angle = 45,
+        hjust = 1,
+        vjust = 1
+      ),
+      legend.key.height = unit(0.5, "line"),
+      legend.text = element_text(size = 8),
+      legend.title = element_blank()
+    ) + ylab("Relative Abundance (FPKM)") + xlab("")
   print(p)
+}, height = 'auto', width = 'auto')
+
+output$dltrxgene <- renderUI({
+  if (!is.null(getgeneid()$cttbl)) {
+    downloadButton('Downloadtregene', 'Download PNG')
+  }
 })
+
+output$Downloadtregene <- downloadHandler(
+  file = function() {
+    paste('tregene', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 160,
+      height = 4 * 120,
+      res = 120,
+      pointsize = 5
+    )
+    if (is.null(getgeneid()$cttbl)) {
+      return()
+    }
+    countTable <- getgeneid()$cttbl
+    par(oma = c(4, 1, 4, 1))
+    p <-
+      ggplot(countTable, aes(x = grptrx, y = log2(value + 1))) + geom_boxplot(aes(fill = factor(grptrx))) + geom_jitter(height = 0) + theme(
+        legend.position = "left",
+        axis.text.x = element_text(
+          angle = 45,
+          hjust = 1,
+          vjust = 1
+        ),
+        legend.key.height = unit(0.5, "line"),
+        legend.text = element_text(size = 8),
+        legend.title = element_blank()
+      ) + ylab("Relative Abundance (FPKM)") + xlab("")
+    print(p)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+
diff --git a/vizapp/tools/altsplice_ui.R b/vizapp/tools/altsplice_ui.R
index 087b3a1..30bd1a9 100644
--- a/vizapp/tools/altsplice_ui.R
+++ b/vizapp/tools/altsplice_ui.R
@@ -1,27 +1,35 @@
 output$ui_altsplice <- renderUI({
-  fluidPage(
-       includeCSS("www/style.css"),
-         sidebarLayout(
-            sidebarPanel(
-                uiOutput("dir.splice"),
-                       textInput("symsearch", "Search By Gene Symbol", 'IL1B'),
-                       textInput("enssearch", "Search By ENS ID",''),
-                       numericInput("kct",label = "Number of Clusters",value = 2),   
-                       actionButton("altButton", "GO")
-                ),
-            mainPanel(
-                tabsetPanel(
-                       tabPanel("Gene Compare",
-                             dataTableOutput('gene.stat'),
-                             dataTableOutput('trx.name'),
-                             plotOutput("plot.cluster"),
-                             plotOutput("trx.gene"),
-                             plotOutput("plot.means")
-                             )
-                    )
-                )
-            )
-        )
-    
+  list(fluidPage(
+    includeCSS("www/style.css"),
+    fluidRow(
+      sidebarPanel(
+        uiOutput("dir.splice"),
+        textInput("symsearch", "Search By Gene Symbol", 'IL1B'),
+        textInput("enssearch", "Search By ENS ID", ''),
+        numericInput("kct", label = "Number of Clusters", value = 2),
+        actionButton("altButton", "GO", class = "btn btn-primary btn-bg centerbtn")
+      ),
+      column(7,
+             tabsetPanel(
+               tabPanel(
+                 "Gene Compare",
+                 br(),br(),
+                 dataTableOutput('gene.stat'),
+                 br(),br(),
+                 dataTableOutput('trx.name'),
+                 br(),
+                 uiOutput('downloadTrx'),
+                 plotOutput("plot.cluster"),
+                 uiOutput('dlplotcluster'),
+                 br(),br(),
+                 plotOutput("trx.gene"),
+                 uiOutput('dltrxgene'),
+                 plotOutput("plot.means", height = 900, width = 'auto'),
+                 uiOutput('dlplotmean')
+               )
+             ))
+    )
+  ))
+  
 })
 
diff --git a/vizapp/tools/dea.R b/vizapp/tools/dea.R
index 1676e6f..de9b93d 100644
--- a/vizapp/tools/dea.R
+++ b/vizapp/tools/dea.R
@@ -1,101 +1,309 @@
 # UI-elements for DEA
 
-ctfile <-  paste(data.dir,'countTable.logCPM.txt',sep='/')
-samfile <-  paste(data.dir,'design.shiny.txt',sep='/')
-cts <- read.table(file=ctfile,header=TRUE,sep='\t')
-samtbl <- read.table(samfile,header=TRUE,sep="\t")
-samples <- colnames(cts[,4:length(cts)])
-mergetbl <- merge(as.data.frame(samples),samtbl,by.x="samples",by.y="SampleID",all.x=TRUE,sort=FALSE)
+ctfile <-  paste(data.dir, 'countTable.logCPM.txt', sep = '/')
+samfile <-  paste(data.dir, 'design.shiny.txt', sep = '/')
+cts <- read.table(file = ctfile, header = TRUE, sep = '\t')
+samtbl <- read.table(samfile, header = TRUE, sep = "\t")
+samples <- colnames(cts[, 4:length(cts)])
+mergetbl <-
+  merge(
+    as.data.frame(samples),
+    samtbl,
+    by.x = "samples",
+    by.y = "SampleID",
+    all.x = TRUE,
+    sort = FALSE
+  )
 grps <- mergetbl$SampleGroup
 grpnames <- levels(factor(grps))
-col.blocks <-col.grp(grps,grpnames)
-MSIG.geneSets <- read.gmt(paste(data.dir,'geneset.shiny.gmt',sep='/'))
+col.blocks <- col.grp(grps, grpnames)
+MSIG.geneSets <-
+  read.gmt(paste(data.dir, 'geneset.shiny.gmt', sep = '/'))
 
 output$pick.dea <- renderUI({
-    flist <- list.files(data.dir,pattern="*edgeR.txt$")
-    selectInput("file", "Choose Pair", choices=flist)
+  flist <- list.files(data.dir, pattern = "*edgeR.txt$")
+  selectInput("file", "Choose Pair", choices=flist, width = "100%")
 })
 output$pick.pathway <- renderUI({
-    pathways <- names(MSIG.geneSets)
-    pathchoices = setNames(1:length(pathways),pathways)
-    selectInput("deapathname", "Choose Pair", choices=pathchoices)
+  pathways <- names(MSIG.geneSets)
+  pathchoices = setNames(1:length(pathways), pathways)
+  selectInput("deapathname", "Choose Pair", choices = pathchoices)
 })
 
 get.data <- function(var) {
-    f <- paste(data.dir,var$file,sep='/')
-    comp <- read.table(f,header=TRUE,sep='\t')
-    comp.filt <- na.omit(comp[abs(comp$logFC) >= var$fc.thresh & comp$rawP <= var$pval.thresh,])
-    if (var$adjust == 'FDR') {
-        comp.filt <- na.omit(comp[abs(comp$logFC) >= var$fc.thresh & comp$fdr <= var$pval.thresh,])
-    }
-    if (var$adjust == 'BONF') {
-        comp.filt <- na.omit(comp[abs(comp$logFC) >= var$fc.thresh & comp$bonf <= var$pval.thresh,])
-    }
-    genelist <- as.character(head(comp.filt[order(comp.filt$fdr),]$symbol,n=var$numgenes))
-    if (var$heatmap == 'hgeneset') {
-        genelist <- unlist(MSIG.geneSets[as.numeric(var$deapathname)])
-    }
-   if (var$heatmap == 'cgeneset') {
-         genelist <- unlist(strsplit(as.character(var$genes), "[;\n]+"))
-   }
-   return(list(filt=comp.filt,glist=genelist))
+  f <- paste(data.dir, var$file, sep = '/')
+ # f <-paste(f, "edgeR.txt", sep = ".") #This line needs to comment out if input is fullname
+  f1 <- paste(data.dir, input$file, sep = '/')
+  hmcomp <-paste("Heatmap of all genes with an FDR < 0.05 using EdgeR Results", sep ='')
+  top50 <- paste("Top 50 User Defined Genes")
+  allgene <- paste("All Differentially Expressed Genes")
+  comp <- read.table(f, header = TRUE, sep = '\t')
+  comp.filt <-
+    na.omit(comp[abs(comp$logFC) >= var$fc.thresh &
+                   comp$rawP <= var$pval.thresh,])
+  if (var$adjust == 'FDR') {
+    comp.filt <-
+      na.omit(comp[abs(comp$logFC) >= var$fc.thresh &
+                     comp$fdr <= var$pval.thresh,])
+  }
+  if (var$adjust == 'BONF') {
+    comp.filt <-
+      na.omit(comp[abs(comp$logFC) >= var$fc.thresh &
+                     comp$bonf <= var$pval.thresh,])
+  }
+  genelist <-
+    as.character(head(comp.filt[order(comp.filt$fdr),]$symbol, n = var$numgenes))
+  if (var$heatmap == 'hgeneset') {
+    genelist <- unlist(MSIG.geneSets[as.numeric(var$deapathname)])
+  }
+  if (var$heatmap == 'cgeneset') {
+    genelist <- unlist(strsplit(as.character(var$genes), "[;\n]+"))
+  }
+  return(
+    list(
+      filt = comp.filt,
+      glist = genelist,
+      f1 = f1,
+      hmcomp = hmcomp,
+      top50 = top50,
+      allgene = allgene
+    )
+  )
 }
 
-tbls <-  eventReactive(input$deButton,{get.data(input)})
+tbls <-  eventReactive(input$deButton,
+                       {
+                         get.data(input)
+                       })
 
 output$selectgenes <- renderUI({
-   symnames <- tbls()$glist
-   textAreaInput("genes", "Gene Symbols separated by ';'",value=paste(symnames,collapse=";"), width = '95%',rows=10)
+  symnames <- tbls()$glist
+  textAreaInput(
+    "genes",
+    "Gene Symbols separated by ';'",
+    value = paste(symnames, collapse = ";"),
+    width = '95%',
+    rows = 10
+  )
 })
 
 output$dge.c <- DT::renderDataTable({
-    t1 <- tbls()$filt
-    t1$symbol <- paste("<a href=http://www.genecards.org/cgi-bin/carddisp.pl?gene=",t1$symbol,'>',t1$symbol,"</a>",sep='')
-    t1$ensembl <- paste("<a href=http://www.ensembl.org/Homo_sapiens/Gene/Summary?g=",t1$ensembl,'>',t1$ensembl,"</a>",sep='')
-    t1
-},escape=FALSE,filter = 'top',options = list(lengthMenu = c(10, 25, 50, 200, -1)))
-
-output$downloadC <- downloadHandler(
-                                     file <- paste(input$file,".filt.txt",sep=""),
-                                     content = function(file) {
-                                       write.table(tbls()$filt,file,quote=FALSE,row.names=FALSE,sep='\t')
-                                     })
+  t1 <- tbls()$filt
+  t1$symbol <-
+    paste(
+      "<a href=http://www.genecards.org/cgi-bin/carddisp.pl?gene=",
+      t1$symbol,
+      '>',
+      t1$symbol,
+      "</a>",
+      sep = ''
+    )
+  t1$ensembl <-
+    paste(
+      "<a href=http://www.ensembl.org/Homo_sapiens/Gene/Summary?g=",
+      t1$ensembl,
+      '>',
+      t1$ensembl,
+      "</a>",
+      sep = ''
+    )
+  t1
+}, escape = FALSE, filter = 'top', options = list(
+  lengthMenu = list(c(10, 25, 50, 100, -1), list('10', '25', '50', '100', 'All')),
+  autoWidth = TRUE,
+  columnDefs = list(list(width = '5%', targets = '0')),
+  scrollX = TRUE
+))
 
+output$downloadC <- renderUI({
+  if (!is.null(tbls()$filt)) {
+    downloadButton('OutputFile', 'Download CSV')
+  }
+})
+output$OutputFile <- downloadHandler(
+  file <- paste(input$file, ".filt.txt", sep = ""),
+  content = function(file) {
+    write.table(
+      tbls()$filt,
+      file,
+      quote = FALSE,
+      row.names = FALSE,
+      sep = '\t'
+    )
+  }
+)
 plotHeatmap <- reactive({
-	syms <- tbls()$glist
-	ct2 <- cts[cts$SYMBOL %in% syms,]
-	subset <- ct2[,4:length(ct2)]
-	row.names(subset) <- ct2$SYMBOL
-	STREE <- hclust(dist(t(subset)))
-      	zscores <- scale(t(subset))
-      	ngenes <- length(colnames(zscores))
-      	textscale <- (1/(ngenes/30))
-      	if (textscale > 1) {
-           textscale <-1
-      	}
-      	if (textscale < 0.1) {
-           textscale <- 0.1
-      	}
-	heatmap.2(zscores, col = bluered(100),Rowv = as.dendrogram(STREE), RowSideColors = col.blocks,dendrogram='row', cexCol=textscale,srtRow=45,srtCol=45,trace="none",margins=c(8,16))
-	legend("topright",legend=grpnames,col=rainbow(length(grpnames)),pch=20)
+  syms <- tbls()$glist
+  ct2 <- cts[cts$SYMBOL %in% syms,]
+  subset <- ct2[, 4:length(ct2)]
+  row.names(subset) <- ct2$SYMBOL
+  STREE <- hclust(dist(t(subset)))
+  zscores <- scale(t(subset))
+  ngenes <- length(colnames(zscores))
+  textscale <- (1 / (ngenes/30))
+  if (textscale > 1) {
+    textscale <- 12
+  }
+  if (textscale < 0.1) {
+    textscale <- 12
+  }
+  if (input$cluster == 2) {
+    heatmap.2(
+      zscores,
+      col = bluered(100),
+      #Rowv = as.dendrogram(STREE),
+      Rowv = FALSE,
+      Colv = FALSE,
+      lwid = c(0.5,3),
+      RowSideColors = col.blocks,
+      dendrogram = 'row',
+      cexCol = 1.1,
+      srtRow = 45,
+      srtCol = 45,
+      trace = "none",
+      margins = c(8, 7)
+    )
+  } else{
+    heatmap.2(
+      zscores,
+      col = bluered(100),
+      Rowv = as.dendrogram(STREE),
+      RowSideColors = col.blocks,
+      dendrogram = 'row',
+      cexCol = 1.1,
+      srtRow = 45,
+      srtCol = 45,
+      lwid = c(0.5,3),
+      trace = "none",
+      margins = c(8, 7)
+    )
+  }
+  legend("top",
+         legend = grpnames,
+         col = rainbow(length(grpnames)),
+         pch = 20)
 })
 output$plot.heatmap <- renderPlot({
-	plotHeatmap()
+  plotHeatmap()
 })
+
+output$dlheatmap <- renderUI({
+  if (!is.null(tbls()$glist)) {
+    downloadButton('Downloadhp', 'Download PNG')
+  }
+})
+
+output$Downloadhp <- downloadHandler(
+  file = function() {
+    paste('mean', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 140,
+      height = 4 * 100,
+      res = 140,
+      pointsize = 5
+    )
+    if (is.null(tbls()$glist)) {
+      return()
+    }
+    syms <- tbls()$glist
+    ct2 <- cts[cts$SYMBOL %in% syms,]
+    subset <- ct2[, 4:length(ct2)]
+    row.names(subset) <- ct2$SYMBOL
+    STREE <- hclust(dist(t(subset)))
+    zscores <- scale(t(subset))
+    ngenes <- length(colnames(zscores))
+    textscale <- (1 / (ngenes/30))
+    if (textscale > 1) {
+      textscale <- 12
+    }
+    if (textscale < 0.1) {
+      textscale <- 12
+    }
+    if (input$cluster == 2) {
+      plot <- heatmap.2(
+        zscores,
+        col = bluered(100),
+        Rowv = FALSE,
+        Colv = FALSE,
+        lwid = c(0.5,3),
+        RowSideColors = col.blocks,
+        dendrogram = 'row',
+        cexCol = 1.1,
+        srtRow = 45,
+        srtCol = 45,
+        trace = "none",
+        margins = c(8, 7)
+      )
+    } else{
+     plot <- heatmap.2(
+        zscores,
+        col = bluered(100),
+        Rowv = as.dendrogram(STREE),
+        RowSideColors = col.blocks,
+        dendrogram = 'row',
+        cexCol = 1.1,
+        srtRow = 45,
+        srtCol = 45,
+        lwid = c(0.5,3),
+        trace = "none",
+        margins = c(8, 7)
+      )
+    }
+    legend("top",
+           legend = grpnames,
+           col = rainbow(length(grpnames)),
+           pch = 20)
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+
 output$downloadpdf = downloadHandler(
-      filename = "output.heatmap.pdf",
-      content = function(file) {
-      pdf(file = file,paper="letter")
-      plotHeatmap()
-      dev.off()
-      })
+  filename = "output.heatmap.pdf",
+  content = function(file) {
+    pdf(file = file, paper = "letter")
+    plotHeatmap()
+    dev.off()
+  }
+)
 
 output$hm.comp <- renderImage({
-  f1 <- paste(data.dir,input$file,sep='/')
-  png <- gsub('edgeR.txt','heatmap.edgeR.png',f1)
-  list(src=png, alt=paste("HeatMap Comparison"))
-},deleteFile=FALSE)
+  f1 <- paste(tbls()$f1)
+  png <- gsub('edgeR.txt', 'heatmap.edgeR.png', f1)
+  list(
+    src = png,
+    alt = paste("HeatMap Comparison"),
+    width = "100%",
+    height = "auto"
+  )
+}, deleteFile = FALSE)
 
-output$hmcomp.desc <- renderText({ 
-      paste("Heatmap of all genes with an FDR < 0.05 using EdgeR Results",sep='')
-    })
+output$dlhmcomp <- renderUI({
+  if (!is.null(tbls()$f1)) {
+    downloadButton('Downloadhm', 'Download PNG')
+  }
+})
+output$Downloadhm <- downloadHandler(
+  file = function() {
+    paste('heatmap_comp', 'png', sep = ".")
+  },
+  content <- function(file) {
+    f1 <- paste(tbls()$f1)
+    png <- gsub('edgeR.txt', 'heatmap.edgeR.png', f1)
+    file.copy(png, file)
+  }
+)
+
+output$hmcomp.allgene <- renderText({
+  paste(tbls()$allgene)
+})
+output$hmcomp.top50 <- renderText({
+  paste(tbls()$top50)
+})
+output$hmcomp.desc <- renderText({
+  paste(tbls()$hmcomp)
+})
diff --git a/vizapp/tools/dea_ui.R b/vizapp/tools/dea_ui.R
index 6c0a448..a0d88eb 100644
--- a/vizapp/tools/dea_ui.R
+++ b/vizapp/tools/dea_ui.R
@@ -1,57 +1,65 @@
-#######################################
-# Shiny interface for data functions
-#######################################
-# data ui and tabs
-output$ui_dea <- renderUI({
-    list(
-        includeCSS("www/style.css"),
-        sidebarLayout(
-            sidebarPanel(
-                numericInput("fc.thresh",
-                             "LogFold Change Threshold:", 1),
-                numericInput("gene.thresh",
-                             "Gene Mean Threshold:", 5),
-                numericInput("pval.thresh",
-                             "P-Value Threshold:", 0.05),
-                selectInput("adjust", "Choose P-Value Correction", choices=c("raw","FDR",'BONF'),selected='FDR'),
-                uiOutput("pick.dea"),
-	     	selectInput(
-			"heatmap", "HeatMap",
-      	     		c(Top = "top",
-               		HallmarkGeneSet = "hgeneset",
-	       		CustomGeneSet= "cgeneset")
-	       	),
-	     	conditionalPanel(
-      	     	condition = "input.heatmap == 'cgeneset'",
-	     		  uiOutput("selectgenes")
-		),
-	     	conditionalPanel(
-      	     	condition = "input.heatmap == 'top'",
-	      	numericInput("numgenes","Number Top Genes:", 50)
-		),
-	     	conditionalPanel(
-      	     	condition = "input.heatmap == 'hgeneset'",
-	     	uiOutput("pick.pathway")
-		),
-	    	actionButton("deButton", "Go")
-	    ),
-            mainPanel(
-                tabsetPanel(
-                    tabPanel("Differential Gene Set Comparison",
-                             downloadButton('downloadC', 'Download CSV'),
-                             dataTableOutput('dge.c')
-                             ),
-                    tabPanel("Heatmap",
-                             #downloadButton('downloadpdf', 'Download Heatmap'),
-			     h1("HeatMap Comparison"),
-			     h3("Top 50 User Defined Genes"),
-			     plotOutput("plot.heatmap"),
-			     h3("All Differentially Expressed Genes"),
-                             imageOutput("hm.comp",width="1200px",height="1200px"),
-			     textOutput("hmcomp.desc")
-                             )
-                    )
-                )
-            )
-        )
-})
+#######################################
+# Shiny interface for data functions
+#######################################
+# data ui and tabs
+output$ui_dea <- renderUI({
+  list(fluidPage(
+    includeCSS("www/style.css"),
+    fluidRow(
+      sidebarPanel(
+        numericInput("fc.thresh",
+                     "LogFold Change Threshold:", 1),
+        numericInput("gene.thresh",
+                     "Gene Mean Threshold:", 5),
+        numericInput("pval.thresh",
+                     "P-Value Threshold:", 0.05),
+        selectInput(
+          "adjust",
+          "Choose P-Value Correction",
+          choices = c("raw", "FDR", 'BONF'),
+          selected = 'FDR'
+        ),
+        uiOutput("pick.dea"),
+        selectInput(
+          "heatmap",
+          "HeatMap",
+          c(
+            Top = "top",
+            HallmarkGeneSet = "hgeneset",
+            CustomGeneSet = "cgeneset"
+          )
+        ),
+        conditionalPanel(condition = "input.heatmap == 'cgeneset'",
+                         uiOutput("selectgenes")),
+        conditionalPanel(condition = "input.heatmap == 'top'",
+                         numericInput("numgenes", "Number Top Genes:", 50)),
+        conditionalPanel(condition = "input.heatmap == 'hgeneset'",
+                         uiOutput("pick.pathway")),
+        radioButtons("cluster", label = "Cluster",
+                     choices = list("Display Cluster" = 1, "Hide Cluster" = 2), 
+                     selected = 1),
+        actionButton("deButton", "Go", class = "btn btn-primary btn-bg centerbtn")
+      ),
+      column(7,
+             tabsetPanel(
+               tabPanel(
+                 "Differential Gene Set Comparison",
+                 br(),br(),
+                 dataTableOutput('dge.c', width = '100%'),
+                 uiOutput('downloadC')
+               ),
+               tabPanel(
+                 "Heatmap Comparison",
+                 #downloadButton('downloadpdf', 'Download Heatmap'),
+                 h3(textOutput("hmcomp.top50")),
+                 plotOutput("plot.heatmap"),
+                 uiOutput("dlheatmap"),
+                 h3(textOutput("hmcomp.allgene")),
+                 imageOutput("hm.comp", width = "100%", height = "auto"),
+                 uiOutput('dlhmcomp'),
+                 textOutput("hmcomp.desc")
+               )
+             ))
+    )
+  ))
+})
diff --git a/vizapp/tools/gc.R b/vizapp/tools/gc.R
index d105b2e..e0bf506 100644
--- a/vizapp/tools/gc.R
+++ b/vizapp/tools/gc.R
@@ -1,60 +1,243 @@
-
-samfile <-  paste(data.dir,'design.shiny.txt',sep='/')
-samtbl <- read.table(samfile,header=TRUE,sep="\t")
+samfile <-  paste(data.dir, 'design.shiny.txt', sep = '/')
+samtbl <- read.table(samfile, header = TRUE, sep = "\t")
 
 output$pick.group <- renderUI({
-    opts <- names(samtbl)
-    selectInput("groupname", "Plot By", choices=opts,selected='SampleGroup')
+  opts <- names(samtbl)
+  selectInput("groupname",
+              "Plot By",
+              choices = opts,
+              selected = 'SampleGroup')
 })
 
 get.ct <- function(var) {
-    ctfile <-  paste(data.dir,'countTable.logCPM.txt',sep='/')
-    statfile <- paste(data.dir,'edgeR.results.txt',sep='/')
-    wp.df <- data.frame(Column1 = c(0), Column2 = c(0))
-    
-    if (nchar(as.vector(var$symsearch)) > 2) {
-      cts <- read.csv.sql(ctfile, sql = paste("select * from file where symbol ='",var$symsearch,"'",sep=''),sep = "\t")
-      if (file.exists(statfile)) {
-        wp.df <- read.csv.sql(statfile, sql = paste("select * from file where symbol ='",var$symsearch,"'",sep=''),sep = "\t")
-      }
+  ctfile <-  paste(data.dir, 'countTable.logCPM.txt', sep = '/')
+  statfile <- paste(data.dir, 'edgeR.results.txt', sep = '/')
+  wp.df <- data.frame(Column1 = c(0), Column2 = c(0))
+  bx <-
+    paste(
+      "Relative Abudance of",
+      input$symsearch,
+      "calculated by Log2(Counts Per Million Reads).  Boxplots draw to represent the 25th and 75th percentile (the lower and upper quartiles, respectively) as a box with a band in the box representing 50th percentile (the median). The upper whisker is located at the 'smaller' of the maximum x value and Q_3 + 1.5 inner quantile range(IRQ), whereas the lower whisker is located at the 'larger' of the smallest x value and Q_1 - 1.5 IQR",
+      sep = ' '
+    )
+  vio <- paste(
+      "Relative Abudance of",
+      input$symsearch,
+      input$enssearch,
+      "calculated by Log2(Counts Per Million Reads).  Violin plot is similar to box plots above, except that it also show the kernel probability density of the data at different value. Violin plots include a marker for the median of the data and a box indicating the interquartile range, as in boxplot above.",
+      sep = ' '
+    )
+  if (nchar(as.vector(var$symsearch)) > 2) {
+    cts <-
+      read.csv.sql(
+        ctfile,
+        sql = paste("select * from file where symbol ='", var$symsearch, "'", sep =
+                      ''),
+        sep = "\t"
+      )
+    if (file.exists(statfile)) {
+      wp.df <-
+        read.csv.sql(
+          statfile,
+          sql = paste(
+            "select * from file where symbol ='",
+            var$symsearch,
+            "'",
+            sep = ''
+          ),
+          sep = "\t"
+        )
     }
-    else {
-      if (nchar(as.vector(var$enssearch)) > 2) {
-        cts <- read.csv.sql(ctfile, sql = paste("select * from file where ENSEMBL ='",var$enssearch,"'",sep=''),sep = "\t")
-        if (file.exists(statfile)) {
-          wp.df <- read.csv.sql(statfile, sql = paste("select * from file where ENSEMBL ='",var$enssearch,"'",sep=''),sep = "\t")
-        }
+  }
+  else {
+    if (nchar(as.vector(var$enssearch)) > 2) {
+      cts <-
+        read.csv.sql(
+          ctfile,
+          sql = paste(
+            "select * from file where ENSEMBL ='",
+            var$enssearch,
+            "'",
+            sep = ''
+          ),
+          sep = "\t"
+        )
+      if (file.exists(statfile)) {
+        wp.df <-
+          read.csv.sql(
+            statfile,
+            sql = paste(
+              "select * from file where ENSEMBL ='",
+              var$enssearch,
+              "'",
+              sep = ''
+            ),
+            sep = "\t"
+          )
       }
     }
-    countTable <- cts[,4:length(cts)]
-    samples <- colnames(countTable)
-    mergetbl <- merge(as.data.frame(samples),samtbl,by.x="samples",by.y="SampleID",all.x=TRUE,sort=FALSE)
-    grps <- mergetbl[,var$groupname]
-    newdf <- data.frame(ct=t(countTable),grp=as.character(grps))
-    names(newdf) = c('cts','grp')
-    return(list(ctable=newdf,tbl=cts,design=samtbl,stats=wp.df))
   }
+  countTable <- cts[, 4:length(cts)]
+  samples <- colnames(countTable)
+  mergetbl <-
+    merge(
+      as.data.frame(samples),
+      samtbl,
+      by.x = "samples",
+      by.y = "SampleID",
+      all.x = TRUE,
+      sort = FALSE
+    )
+  grps <- mergetbl[, var$groupname]
+  newdf <- data.frame(ct = t(countTable), grp = as.character(grps))
+  names(newdf) = c('cts', 'grp')
+  return(list(
+    ctable = newdf,
+    tbl = cts,
+    design = samtbl,
+    stats = wp.df,
+    bx = bx,
+    vio = vio
+  ))
+}
 
-forct <- eventReactive(input$gcButton,{get.ct(input)})
+forct <- eventReactive(input$gcButton, {
+  get.ct(input)
+})
 
 output$plot.gene <- renderPlot({
+  countTable <- forct()$ctable
+  par(oma = c(4, 4, 1, 1))
+  grpnames <- levels(factor(as.character(countTable$grp)))
+  #boxplot(
+  # countTable$cts ~ countTable$grp,
+  # col = rainbow(length(grpnames)),
+  #cex.axis = 0.7,
+  # ylab = 'Relative Abundance (logCPM)',
+  # las = 1,
+  # main = input$groupname
+  # )
+  p <-
+    ggplot(countTable, aes(x = grp, y = cts))  + ggtitle(input$groupname) +
+    theme(plot.title = element_text(
+      hjust = 0.5,
+      size = 18,
+      margin = margin(b = 20, unit = "pt")
+    ))  + geom_boxplot(trim = FALSE, aes(fill = factor(grp))) + theme(legend.position =
+                                                                        "none",
+                                                                      axis.title.y = element_text(size=14), 
+                                                                      axis.text.y = element_text(size=14), 
+                                                                      axis.text.x = element_text(
+                                                                        angle = 45,
+                                                                        hjust = 1,
+                                                                        vjust = 1,
+                                                                        size=14
+                                                                      )) + ylab("Relative Abundance (logCPM)") + xlab("")
+  print(p)
+}, height = "auto", width = 'auto')
+
+output$dlboxplot <- renderUI({
+  if (!is.null(forct()$ctable)) {
+    downloadButton('Downloadbp', 'Download PNG')
+  }
+})
+output$Downloadbp <- downloadHandler(
+  file = function() {
+    paste('boxplot', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 120,
+      res = 120,
+      pointsize = 5
+    )
+    if (is.null(forct()$ctable)) {
+      return()
+    }
     countTable <- forct()$ctable
-    par(oma=c(4,4,1,1)) 
+    par(oma = c(4, 4, 1, 1))
     grpnames <- levels(factor(as.character(countTable$grp)))
-    boxplot(countTable$cts ~ countTable$grp,col=rainbow(length(grpnames)),cex.axis=0.7,ylab='Relative Abundance (logCPM)',las=2,main=input$groupname)
-    })
+    plot <-
+      ggplot(countTable, aes(x = grp, y = cts))  + ggtitle(input$groupname) +
+      theme(plot.title = element_text(
+        hjust = 0.5,
+        size = 18,
+        margin = margin(b = 20, unit = "pt")
+      ))  + geom_boxplot(trim = FALSE, aes(fill = factor(grp))) + theme(legend.position =
+                                                                          "none",
+                                                                        axis.text.x = element_text(
+                                                                          angle = 45,
+                                                                          hjust = 1,
+                                                                          vjust = 1
+                                                                        )) + ylab("Relative Abundance (logCPM)") + xlab("")
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
 
-output$bxplot.desc <- renderText({ 
-      paste("Relative Abudance of",input$symsearch,"calculated by Log2(Counts Per Million Reads).  Boxplots draw to represent the 25th and 75th percentile (the lower and upper quartiles, respectively) as a box with a band in the box representing 50th percentile (the median). The upper whisker is located at the 'smaller' of the maximum x value and Q_3 + 1.5 inner quantile range(IRQ), whereas the lower whisker is located at the 'larger' of the smallest x value and Q_1 - 1.5 IQR",sep=' ')
-    })
+output$bxplot.desc <- renderText({
+  paste(forct()$bx)
+})
 
 output$violin.gene <- renderPlot({
   countTable <- forct()$ctable
-  par(oma=c(4,4,1,1))
-  p <- ggplot(countTable,aes(x=grp,y=cts)) + geom_violin(trim=FALSE,aes(fill = factor(grp))) + geom_jitter(height = 0) + theme(legend.position="none",axis.text.x=element_text(angle=45,hjust=1, vjust=1)) + ylab("Relative Abundance (logCPM)") + xlab("")
+  par(oma = c(4, 4, 1, 1))
+  p <-
+    ggplot(countTable, aes(x = grp, y = cts)) + geom_violin(trim = FALSE, aes(fill = factor(grp))) + geom_jitter(height = 0) + theme(legend.position =
+                                                                                                                                       "none",
+                                                                                                                                     axis.title.y = element_text(size=14), 
+                                                                                                                                     axis.text.y = element_text(size=14), 
+                                                                                                                                     axis.text.x = element_text(
+                                                                                                                                       angle = 45,
+                                                                                                                                       hjust = 1,
+                                                                                                                                       vjust = 1,
+                                                                                                                                       size = 14
+                                                                                                                                     )) + ylab("Relative Abundance (logCPM)") + xlab("")
   print(p)
-}, height = 400, width = 900)
+}, height = "auto", width = 'auto')
+
+output$dlviolinplot <- renderUI({
+  if (!is.null(forct()$ctable)) {
+    downloadButton('Downloadvp', 'Download PNG')
+  }
+})
 
-output$violin.desc <- renderText({ 
-      paste("Relative Abudance of",input$symsearch,input$enssearch,"calculated by Log2(Counts Per Million Reads).  Violin plot is similar to box plots above, except that it also show the kernel probability density of the data at different value. Violin plots include a marker for the median of the data and a box indicating the interquartile range, as in boxplot above.",sep=' ')
-    })
+output$Downloadvp <- downloadHandler(
+  file = function() {
+    paste('violinplot', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 120,
+      res = 120,
+      pointsize = 5
+    )
+    if (is.null(forct()$ctable)) {
+      return()
+    }
+    countTable <- forct()$ctable
+    par(oma = c(4, 4, 1, 1))
+    grpnames <- levels(factor(as.character(countTable$grp)))
+    par(oma = c(4, 4, 1, 1))
+    plot <-
+      ggplot(countTable, aes(x = grp, y = cts)) + geom_violin(trim = FALSE, aes(fill = factor(grp))) + geom_jitter(height = 0) + theme(legend.position =
+                                                                                                                                         "none",
+                                                                                                                                       axis.text.x = element_text(
+                                                                                                                                         angle = 45,
+                                                                                                                                         hjust = 1,
+                                                                                                                                         vjust = 1
+                                                                                                                                       )) + ylab("Relative Abundance (logCPM)") + xlab("")
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+
+output$violin.desc <- renderText({
+  paste(forct()$vio)
+})
diff --git a/vizapp/tools/gc_ui.R b/vizapp/tools/gc_ui.R
index 4840ade..b9903c0 100644
--- a/vizapp/tools/gc_ui.R
+++ b/vizapp/tools/gc_ui.R
@@ -1,26 +1,33 @@
 output$ui_gc <- renderUI({
-    fluidPage(
-        includeCSS("www/style.css"),
-        sidebarLayout(
-            sidebarPanel(
-                uiOutput("pick.group"),
-                textInput("symsearch", "Search By Gene Symbol", 'IL1B'),
-                textInput("enssearch", "Search By ENS ID",''),
-                actionButton("gcButton", "GO")
-                ),
-            mainPanel(
-                tabsetPanel(
-                    tabPanel("Gene Compare",
-                             dataTableOutput('gc.stats'),
-                             plotOutput("plot.gene"),
-                             textOutput("bxplot.desc"),
-                             plotOutput("violin.gene"),
-                             textOutput("violin.desc")
-			     )
-                    )
-                )
-            )
-        )
-    
+  list(fluidPage(
+    includeCSS("www/style.css"),
+    fluidRow(
+      sidebarPanel(
+        uiOutput("pick.group"),
+        textInput("symsearch", "Search By Gene Symbol", 'IL1B'),
+        textInput("enssearch", "Search By ENS ID", ''),
+        actionButton("gcButton", "GO", class = "btn btn-primary btn-bg centerbtn")
+      ),
+      column(7,
+             tabsetPanel(
+               tabPanel(
+                 "Gene Compare",
+                 dataTableOutput('gc.stats'),
+                 br(),
+                 plotOutput("plot.gene"),
+                 uiOutput('dlboxplot'),
+                 br(),
+                 textOutput("bxplot.desc"),
+                 br(),
+                 plotOutput("violin.gene"),
+                 uiOutput('dlviolinplot'),
+                 br(),
+                 textOutput("violin.desc")
+               )
+             )),
+      tags$style(type='text/css', "#dlboxplot { width:100%;margin-left: 35px;}"),
+      tags$style(type='text/css', "#dlviolinplot { width:100%;margin-left: 35px;}")
+    )
+  ))
+  
 })
-
diff --git a/vizapp/tools/gsea.R b/vizapp/tools/gsea.R
index a3d0a7b..ca19618 100644
--- a/vizapp/tools/gsea.R
+++ b/vizapp/tools/gsea.R
@@ -1,33 +1,96 @@
-
-output$quresult <- renderUI({
-    flist <- list.files(data.dir,pattern="*qusage.rda$")
-    selectInput('fname', "Choose Comparison", choices=flist)
-})
-
-updateData <- function(input) {
-    f1 <- paste(data.dir,input$fname,sep='/')
-    load(file = f1, envir = .GlobalEnv)
-    results <- qsTable(qs.results,number=100,sort.by='fdr')
-    return(list(obj=qs.results,tbl=results))
-}
-values <-  eventReactive(input$quButton,{updateData(input)})
-
-output$gset <- renderUI({
-    tbl <- values()$tbl
-    choices = setNames(row.names(tbl),tbl$pathway.name)	    
-    selectInput("pathname", "Choose Pathway", choices=choices)
-})
-
-output$gsea.tbl <- renderDataTable({
-    values()$tbl
-})
-
-output$plot.cis <- renderPlot({
-    qs.results <- values()$obj
-    plotCIsGenes(qs.results,path.index=as.numeric(input$pathname))
-})
-
-output$plot.genedist <- renderPlot({
-    qs.results <- values()$obj
-    plotGeneSetDistributions(qs.results,path.index=as.numeric(input$pathname))
-})    
+
+output$quresult <- renderUI({
+    flist <- list.files(data.dir,pattern="*qusage.rda$")
+    selectInput('fname', "Choose Comparison", choices=flist)
+})
+
+updateData <- function(input) {
+    f1 <- paste(data.dir,input$fname,sep='/')
+    load(file = f1, envir = .GlobalEnv)
+    results <- qsTable(qs.results,number=100,sort.by='fdr')
+    return(list(obj=qs.results,tbl=results))
+}
+values <-  eventReactive(input$quButton,{updateData(input)})
+
+output$gset <- renderUI({
+    tbl <- values()$tbl
+    choices = setNames(row.names(tbl),tbl$pathway.name)	    
+    selectInput("pathname", "Choose Pathway", choices=choices)
+})
+
+output$gsea.tbl <- renderDataTable({
+  values()$tbl
+})
+output$downloadGS <- renderUI({
+  if(!is.null(values()$tbl)){
+    downloadButton('DownloadGS', 'Download CSV')
+  }
+})
+output$DownloadGS <- downloadHandler(
+  file <- paste(input$fname,".txt",sep=""),
+  content = function(file) {
+    write.table(values()$tbl,file,quote=FALSE,row.names=FALSE,sep='\t')
+  })
+output$plot.cis <- renderPlot({
+    qs.results <- values()$obj
+    plotCIsGenes(qs.results,path.index=as.numeric(input$pathname), cex.xaxis = 1.3)
+})
+output$dlcis <- renderUI({
+   if (!is.null(values()$obj)) {
+  downloadButton('Downloadcis', 'Download PNG')
+  }
+})
+output$Downloadcis <- downloadHandler(
+  file = function() {
+    paste('cisplot', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 120,
+      res = 120,
+      pointsize = 5
+    )
+    if (is.null(values()$obj)) {
+      return()
+    }
+    qs.results <- values()$obj
+    plot <- plotCIsGenes(qs.results,path.index=as.numeric(input$pathname), cex.xaxis = 1.3)
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
+output$plot.genedist <- renderPlot({
+    qs.results <- values()$obj
+    plotGeneSetDistributions(qs.results,path.index=as.numeric(input$pathname), cex =1.6)
+})    
+
+output$dlgenedist <- renderUI({
+  if (!is.null(values()$obj)) {
+    downloadButton('Downloadgenedist', 'Download PNG')
+  }
+})
+output$Downloadgenedist <- downloadHandler(
+  file = function() {
+    paste('cisplot', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 4 * 120,
+      res = 140,
+      pointsize = 5
+    )
+    if (is.null(values()$obj)) {
+      return()
+    }
+    qs.results <- values()$obj
+    plot <- plotGeneSetDistributions(qs.results,path.index=as.numeric(input$pathname), cex =1.6)
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
diff --git a/vizapp/tools/gsea_ui.R b/vizapp/tools/gsea_ui.R
index 226b0ae..8385253 100644
--- a/vizapp/tools/gsea_ui.R
+++ b/vizapp/tools/gsea_ui.R
@@ -1,23 +1,29 @@
 output$ui_gsea <- renderUI({
-    list(
-        includeCSS("www/style.css"),
-        sidebarLayout(
-            sidebarPanel(
-                uiOutput("quresult"),
-                uiOutput("gset"),
-		actionButton("quButton", "Go")
-                ),
-            mainPanel(
-                tabsetPanel(
-                    tabPanel("Gene Set Comparisons",
-                             dataTableOutput('gsea.tbl')
-                             ),
-                    tabPanel("Gene Set Comparison",
-                             plotOutput("plot.cis"),
-                             plotOutput("plot.genedist")
-                             )
-                    )
-                )
-            )
-        )
+  list(fluidPage(
+    includeCSS("www/style.css"),
+    fluidRow(
+      sidebarPanel(
+        uiOutput("quresult"),
+        uiOutput("gset"),
+        actionButton("quButton", "Go", class = "btn btn-primary btn-bg centerbtn")
+      ),
+      column(7,
+             tabsetPanel(
+               tabPanel(
+                 "Gene Set Comparisons",
+                 br(),
+                 br(),
+                 dataTableOutput('gsea.tbl'),
+                 uiOutput("downloadGS")
+               ),
+               tabPanel(
+                 "Gene Set Comparison",
+                 plotOutput("plot.cis"),
+                 uiOutput("dlcis"),
+                 plotOutput("plot.genedist"),
+                 uiOutput("dlgenedist")
+               )
+             ))
+    )
+  ))
 })
diff --git a/vizapp/tools/intro.R b/vizapp/tools/intro.R
index 56a610d..fca052e 100644
--- a/vizapp/tools/intro.R
+++ b/vizapp/tools/intro.R
@@ -1,25 +1,24 @@
-output$ui_intro <- renderUI({
-    list(
-        includeCSS("www/style.css"),
-        sidebarLayout(
-            sidebarPanel(
-                ),
-            mainPanel(
-                h1("Welcome to the RNASeq Analysis Portal", align = "center"),
-                br(),
-                br(),
-                h4("To Compare Gene Abundances Use Gene Compare", align = "center"),
-                p("Here you will be able explore gene abundances by (1) Transmembrane Proteins, (2) Transcription Fractors and (3) Chemocytokines.  Also you can compare the gene abundances of genes by Available Clinicial Data",style = "color:red"),
-                h4("To Examine Differential Gene Analysis Use DEA", align = "center"),
-                p("Here you will be able explore Differential Gene Expresss by Group.  You will also be able to compare two comparisons: such as Case1 vs Control and Case2 vs Control.",style = "color:red"),
-                h4("To Examine Gene Set Enrichment Analysis Use GSEA", align = "center"),
-                p("Here you will be able explore Gene Set Enrichment Analysis by Group and Gene Set List.",style = "color:red"),
-                br(),
-                br(),
-                p("Note:Error messages can indicate data processing or missing data.  Please wait 30 seconds for the program to catch up to any changes in data loading."),
-                h6("Questions? Contract Brandi Cantarel brandi.cantarel@baylorhealth.edu")
-                )
-            )
-        )
-    
+# x <- reactiveVal(1)
+observeEvent(input$actionbtgc, {
+  #x(x() + 1)
+  # if (input$actionbtgc > 0){
+  # updateNavbarPage(session, "rnaseqnav", selected = "panelgc")
+  #   output$Text <-renderText({"lailailailailaillai"})
+  #}
+  updateNavbarPage(session, 'nav_shinyapp', 'panelgc')
 })
+
+observeEvent(input$actionbtdea, {
+  updateNavbarPage(session, 'nav_shinyapp', 'paneldea')
+})
+
+observeEvent(input$actionbtgsea, {
+  updateNavbarPage(session, 'nav_shinyapp', 'panelgsea')
+})
+# output$tb1 <- renderPrint({x()})
+#  output$tb1 <- renderText({
+#   updateNavbarPage(session, '')
+# })
+# output$ui_intro <-renderUI({
+#  source('tools/gc.R', local = TRUE)
+#})
diff --git a/vizapp/tools/intro_ui.R b/vizapp/tools/intro_ui.R
new file mode 100644
index 0000000..cd8ea85
--- /dev/null
+++ b/vizapp/tools/intro_ui.R
@@ -0,0 +1,120 @@
+output$ui_intro <- renderUI({
+  list(
+    #includeCSS("www/style.css"),
+    tags$link(rel = "stylesheet", type = "text/css", href = "style.css"),
+    fluidPage(id = 'intropage',
+              fluidRow(
+                br(),
+                column(
+                  8,
+                  offset = 2,
+                  h1("Welcome to the RNASeq Analysis Portal", align = "center"),
+                  br(),
+                  br(),
+                  div(column(
+                    4,
+                    div(
+                      class = "card text-center",
+                      div(class = "card-header",
+                          "Gene Compare"),
+                      div(
+                        class = "card-body",
+                        h5(
+                          class = "card-title",
+                          "To Compare Gene Abundances",
+                          align = "center"
+                        ),
+                        p(
+                          class = "card-text",
+                          "Here you will be able explore gene abundances by (1) Transmembrane Proteins, (2) Transcription Fractors and (3) Chemocytokines.  Also you can compare the gene abundances of genes by Available Clinicial Data"
+                        )
+                      ),
+                      div(
+                        class = "card-footer",
+                        # a(class="btn btn-primary btn-sm", 'data-toggle'="tab", 'data-value'="Gene Compare", 'id'="btgc", "Gene Compare")
+                        actionButton(
+                          class = "btn btn-primary btn-sm",
+                          inputId = "actionbtgc",
+                          label = "Gene Compare",
+                          icon = NULL
+                        )
+                      )
+                    )
+                  ),
+                  column(
+                    4,
+                    div(
+                      class = "card text-center",
+                      div(class = "card-header",
+                          "DEA"),
+                      div(
+                        class = "card-body",
+                        h5(class = "card-title", "To Examine Differential Gene Analysis"),
+                        p(
+                          class = "card-text",
+                          "Here you will be able explore Differential Gene Expresss by Group.  You will also be able to compare two comparisons: such as Case1 vs Control and Case2 vs Control."
+                        )
+                      ),
+                      div(
+                        class = "card-footer",
+                        # a(class="btn btn-primary btn-sm", 'data-toggle'="tab",'data-value'="DEA",id="dea","DEA")
+                        actionButton(
+                          class = "btn btn-primary btn-sm",
+                          inputId = "actionbtdea",
+                          label = "DEA",
+                          icon = NULL
+                        )
+                      )
+                    )
+                  ),
+                  column(
+                    4,
+                    div(
+                      class = "card text-center",
+                      div(class = "card-header",
+                          "QuSAGE"),
+                      div(
+                        class = "card-body",
+                        h5(class = "card-title", "To Examine Gene Set Enrichment Analysis"),
+                        p(
+                          class = "card-text",
+                          "Here you will be able explore Gene Set Enrichment Analysis by Group and Gene Set List."
+                        )
+                      ),
+                      div(
+                        class = "card-footer",
+                        #a(class="btn btn-primary btn-sm",'data-toggle'="tab", 'data-value'="QuSAGE",id="gsea","GSEA")
+                        actionButton(
+                          class = "btn btn-primary btn-sm",
+                          inputId = "actionbtgsea",
+                          label = "QuSAGE"
+                        )
+                      )
+                    )
+                  ))
+                )
+              ),
+              fluidRow(column(
+                8, offset = 2,
+                br(),
+                br(),
+                div(
+                  class = "alert alert-info",
+                  a(
+                    icon("new-window", lib = "glyphicon"),
+                    strong("CITATION LINK"),
+                    href = "https://git.biohpc.swmed.edu/BICF/Astrocyte/rnaseq",
+                    target = "_blank",
+                    style = "color:white"
+                  ),
+                  p(
+                    strong("Note:"),
+                    "Error messages can indicate data processing or missing data.  Please wait 30 seconds for the program to catch up to any changes in data loading.",
+                    style = "font-size:14px"
+                  )
+                )
+              )))
+    
+  )
+  
+})
diff --git a/vizapp/tools/qc.R b/vizapp/tools/qc.R
index 0a472e0..43a1728 100644
--- a/vizapp/tools/qc.R
+++ b/vizapp/tools/qc.R
@@ -1,40 +1,207 @@
 get.qc <- function(var) {
-    ctfile <-  paste(data.dir,'countTable.stats.txt',sep='/')
-    alfile <-  paste(data.dir,'alignment.summary.txt',sep='/')
-    stats <- read.table(file=ctfile,header=TRUE,sep='\t')
-    align <- read.table(file=alfile,header=TRUE,sep='\t')
-    return(list(featurestat=stats,alignstat=align))
-  } 
+  ctfile <-  paste(data.dir, 'countTable.stats.txt', sep = '/')
+  alfile <-  paste(data.dir, 'alignment.summary.txt', sep = '/')
+  stats <- read.table(file = ctfile,header = TRUE,sep = '\t')
+  align <- read.table(file = alfile,header = TRUE,sep = '\t')
+  fsdes <- paste(
+      "Percent of Total Reads for each gene type.  Boxplots draw to represent the 25th and 75th percentile (the lower and upper quartiles, respectively) as a box with a band in the box representing 50th percentile (the median). The upper whisker is located at the 'smaller' of the maximum x value and Q_3 + 1.5 inner quantile range(IRQ), whereas the lower whisker is located at the 'larger' of the smallest x value and Q_1 - 1.5 IQR",
+      sep = ' '
+    )
+  pca <- paste(data.dir, 'pca.png', sep = "/")
+  mds <- paste(data.dir, 'mds.png', sep = "/")
+  sheat <- paste(data.dir, 'samples_heatmap.png', sep = "/")
+  return(
+    list(
+      featurestat = stats,
+      alignstat = align,
+      fsdes = fsdes,
+      pca = pca,
+      mds = mds,
+      sheat = sheat
+    )
+  )
+}
 
-forstat <- eventReactive(input$qcButton,{get.qc(input)})
+forstat <- eventReactive(input$qcButton, {get.qc(input)})
 
 output$plot.fs <- renderPlot({
+  countTable <- forstat()$featurestat
+  grpnames <- levels(factor(as.character(countTable$Type)))
+  boxplot(
+    countTable$ReadPerc ~ countTable$Type,
+    col = rainbow(length(grpnames)),
+    cex.axis = 0.7,
+    ylab = 'Percent of Total Reads',
+    las = 2,
+    par(mar = c(12, 5, 2, 2))
+  )
+}, height = "auto", width = 'auto')
+
+#Download Button for plot.fs
+output$dlplot <- renderUI({
+  if (!is.null(forstat()$featurestat)) {
+    downloadButton('Downloadplot', 'Download PNG')
+  }
+})
+output$Downloadplot <- downloadHandler(
+  file = function() {
+    paste('plot', 'png', sep = ".")
+  },
+  content <- function(file) {
+    png(
+      file,
+      width = 8 * 120,
+      height = 5 * 120,
+      res = 200,
+      pointsize = 6
+    )
+    if (is.null(forstat()$featurestat)) {
+      return()
+    }
     countTable <- forstat()$featurestat
-    par(oma=c(4,4,1,1)) 
+    par(oma = c(4, 4, 1, 1))
     grpnames <- levels(factor(as.character(countTable$Type)))
-    boxplot(countTable$ReadPerc ~ countTable$Type,col=rainbow(length(grpnames)),cex.axis=0.7,ylab='Percent of Total Reads',las=2)
-  }, height = 400, width = 900)
+    plot <- boxplot(
+      countTable$ReadPerc ~ countTable$Type,
+      col = rainbow(length(grpnames)),
+      cex.axis = 0.7,
+      ylab = 'Percent of Total Reads',
+      las = 2,
+      par(mar = c(12, 5, 2, 2))
+    )
+    print(plot)
+    dev.off()
+  },
+  contentType = "image/png"
+)
 
-output$fs.desc <- renderText({ 
-      paste("Percent of Total Reads for each gene type.  Boxplots draw to represent the 25th and 75th percentile (the lower and upper quartiles, respectively) as a box with a band in the box representing 50th percentile (the median). The upper whisker is located at the 'smaller' of the maximum x value and Q_3 + 1.5 inner quantile range(IRQ), whereas the lower whisker is located at the 'larger' of the smallest x value and Q_1 - 1.5 IQR",sep=' ')
-    })
+#display description for the plot
+output$fs.desc <- renderText({
+  paste(forstat()$fsdes)
+})
 
 output$feature.stats <- DT::renderDataTable({
   t1 <- forstat()$featurestat
-  t1
-},escape=FALSE,filter = 'top',options = list(lengthMenu = c(10, 25, 50, 200, -1)))
+  DT::datatable(
+    t1,
+    escape = FALSE,
+    filter = 'top',
+    options = list(lengthMenu = list(
+      c(10, 25, 50, 100,-1), list('10', '25', '50', '100', 'All')
+    ))
+  )
+})
 
 output$align.stats <- DT::renderDataTable({
   t1 <- forstat()$alignstat
-  t1
-},escape=FALSE,filter = 'top',options = list(lengthMenu = c(10, 25, 50, 200, -1)))
+  DT::datatable(
+    t1,
+    escape = FALSE,
+    filter = 'top',
+    options = list(lengthMenu = list(
+      c(10, 25, 50, 100,-1), list('10', '25', '50', '100', 'All')
+    ))
+  )
+})
+output$downloadAlign <- renderUI({
+  if (!is.null(forstat()$alignstat)) {
+    downloadButton('DownloadAlign', 'Download CSV')
+  }
+})
+output$DownloadAlign <- downloadHandler(
+  file <- paste('alignment.summary.txt'),
+  content = function(file) {
+    write.table(
+      forstat()$alignstat,
+      file,
+      quote = FALSE,
+      row.names = FALSE,
+      sep = '\t'
+    )
+  }
+)
 
+output$downloadGT <- renderUI({
+  if (!is.null(forstat()$featurestat)) {
+    downloadButton('DownloadGT', 'Download CSV')
+  }
+})
+output$DownloadGT <- downloadHandler(
+  file <- paste('countTable.stats.txt'),
+  content = function(file) {
+    write.table(
+      forstat()$featurestat,
+      file,
+      quote = FALSE,
+      row.names = FALSE,
+      sep = '\t'
+    )
+  }
+)
 output$pca1 <- renderImage({
-    list(src=paste(data.dir,'pca.png',sep="/"), alt=paste("Sample Comparison 1"))
-},deleteFile=FALSE)
+  list(
+    src = forstat()$pca,
+    alt = paste("Sample Comparison 1"),
+    width = "100%",
+    height = "100%"
+  )
+}, deleteFile = FALSE)
+
+output$dlpca <- renderUI({
+  if (!is.null(forstat()$pca)) {
+    downloadButton('Downloadpca', 'Download PNG')
+  }
+})
+output$Downloadpca <- downloadHandler(
+  file = function() {
+    paste('pca_analysis', 'png', sep = ".")
+  },
+  content <- function(file) {
+    file.copy(forstat()$pca, file)
+  }
+)
+
 output$pca2 <- renderImage({
-    list(src=paste(data.dir,'mds.png',sep="/"), alt=paste("Sample Comparison 2"))
-},deleteFile=FALSE)
+  list(
+    src = forstat()$mds,
+    alt = paste("Sample Comparison 2"),
+    width = "100%",
+    height = "auto"
+  )
+}, deleteFile = FALSE)
+
+output$dlmds <- renderUI({
+  if (!is.null(forstat()$mds)) {
+    downloadButton('Downloadmds', 'Download PNG')
+  }
+})
+output$Downloadmds <- downloadHandler(
+  file = function() {
+    paste('mds', 'png', sep = ".")
+  },
+  content <- function(file) {
+    file.copy(forstat()$mds, file)
+  }
+)
 output$hmap <- renderImage({
-    list(src=paste(data.dir,'samples_heatmap.png',sep="/"), alt=paste("Sample Comparison 3"))
-},deleteFile=FALSE)
+  list(
+    src = forstat()$sheat,
+    alt = paste("Sample Comparison 3"),
+    width = "100%",
+    height = "auto"
+  )
+}, deleteFile = FALSE)
+
+output$dlhmap <- renderUI({
+  if (!is.null(forstat()$sheat)) {
+    downloadButton('Downloadhmap', 'Download PNG')
+  }
+})
+output$Downloadhmap <- downloadHandler(
+  file = function() {
+    paste('sample_distance', 'png', sep = ".")
+  },
+  content <- function(file) {
+    file.copy(forstat()$sheat, file)
+  }
+)
\ No newline at end of file
diff --git a/vizapp/tools/qc_ui.R b/vizapp/tools/qc_ui.R
index b9aad7b..5c9168c 100644
--- a/vizapp/tools/qc_ui.R
+++ b/vizapp/tools/qc_ui.R
@@ -1,37 +1,53 @@
 output$ui_qc <- renderUI({
-    fluidPage(
-        includeCSS("www/style.css"),
-        sidebarLayout(
-            sidebarPanel(
-                uiOutput("dir.qc"),
-                actionButton("qcButton", "GO")
-                ),
-            mainPanel(
-                tabsetPanel(
-                     tabPanel("Align Stats",
-                             dataTableOutput('align.stats')
-			     ),
-		tabPanel("Gene Type Stats",
-                             dataTableOutput('feature.stats'),
-                             plotOutput("plot.fs"),
-                             textOutput("fs.desc")
-			     ),
-		    tabPanel("MDS ANALYSIS",
-                             h1("MDS"),
-                             imageOutput("pca2",width="1200px",height="1200px")
-                             ),
-		    tabPanel("Sample Distances",
-                             h1("Sample Distances"),
-                             imageOutput("hmap",width="1200px",height="1200px")
-                             ),
-                    tabPanel("PCA ANALYSIS",
-                             h1("PCA"),
-                             imageOutput("pca1",width="1200px",height="1200px")
-                             )
-                    )
-                )
-            )
+  list(fluidPage(
+    includeCSS("www/style.css"),
+    fluidRow(
+      sidebarPanel(
+        uiOutput("dir.qc"),
+        p("Click it to load data"),
+        actionButton("qcButton", "GO",  class = "btn btn-primary btn-bg centerbtn")
+      ),
+      column(7,
+        tabsetPanel(
+          tabPanel(
+            "Align Stats",
+            br(),br(),
+            dataTableOutput('align.stats'),
+            br(),
+            uiOutput('downloadAlign')
+          ),
+          
+          tabPanel(
+            "Gene Type Stats",
+            br(),br(),
+            dataTableOutput('feature.stats'),
+            uiOutput('downloadGT'),
+            plotOutput("plot.fs"),
+            uiOutput('dlplot'),
+            br(),
+            textOutput("fs.desc")
+          ),
+          tabPanel(
+            "MDS Analysis",
+            br(),br(),
+            imageOutput("pca2", width = "100%", height = "auto"),
+            uiOutput('dlmds')
+          ),
+          tabPanel(
+            "Sample Distances",
+            br(),br(),
+            imageOutput("hmap", width = "100%", height = "auto"),
+            uiOutput('dlhmap')
+          ),
+          tabPanel(
+            "PCA Analysis",
+            br(),br(),
+            imageOutput("pca1", width = "100%", height = "auto"),
+            uiOutput('dlpca')
+          )
         )
+      )
+    )
     
+  ))
 })
-
diff --git a/vizapp/ui.R b/vizapp/ui.R
index 3afa28a..defef96 100755
--- a/vizapp/ui.R
+++ b/vizapp/ui.R
@@ -1,14 +1,38 @@
 library(shiny)
-
-shinyUI(navbarPage("RNASeq Analysis",
-                   id = "nav_shinyapp", inverse = TRUE, collapsible = TRUE,
-                   tabPanel("Introduction",uiOutput('ui_intro')),
-		   tabPanel("Dataset QC", uiOutput('ui_qc')),
-                   #tabPanel("Sample Sequencing QC", uiOutput('ui_fastqc')),
-		   tabPanel("Gene Compare", uiOutput('ui_gc')),
-                   tabPanel("Gene Alt Splicing", uiOutput('ui_altsplice')),
-                   tabPanel("DEA", uiOutput('ui_dea')),
-                   tabPanel("QuSAGE", uiOutput('ui_gsea'))
-                   ))
-
-
+library(shinythemes)
+shinyUI(list(
+  navbarPage(
+    title = "RNASeq Analysis",
+    id = "nav_shinyapp",
+    inverse = TRUE,
+    collapsible = TRUE,
+    theme = shinytheme("yeti"),
+    
+    tabPanel("Introduction", uiOutput('ui_intro')),
+    tabPanel("Dataset QC", uiOutput('ui_qc')),
+    #tabPanel("Sample Sequencing QC", uiOutput('ui_fastqc')),
+    tabPanel(
+      "Gene Compare",
+      id = "panelgc",
+      value = "panelgc",
+      uiOutput('ui_gc')
+    ),
+    tabPanel("Gene Alt Splicing", uiOutput('ui_altsplice')),
+    tabPanel("DEA", id = "paneldea", value = "paneldea", uiOutput('ui_dea')),
+    tabPanel(
+      "QuSAGE",
+      id = "panelgsea",
+      value = "panelgsea",
+      uiOutput('ui_gsea')
+    )
+  ),
+  fluidRow(style = "margin-top:40px", tags$footer(class = "footer",
+                                                  div(class = "container",
+                                                      style = "padding-bottom:0; margin-bottom:0",
+                                                        p(icon("envelope", lib = "glyphicon"),
+                                                          "brandi.cantarel@utsouthwestern.edu  |  @ UT Southwestern Medical Center",
+                                                           style = "margin-bottom:-40px;")
+                                                      )
+                                                  )
+           )
+))
diff --git a/vizapp/www/bootstrap.min.css b/vizapp/www/bootstrap.min.css
new file mode 100644
index 0000000..078c429
--- /dev/null
+++ b/vizapp/www/bootstrap.min.css
@@ -0,0 +1,13 @@
+/*!
+ * Bootswatch v4.0.0
+ * Homepage: https://bootswatch.com
+ * Copyright 2012-2018 Thomas Park
+ * Licensed under MIT
+ * Based on Bootstrap
+*//*!
+ * Bootstrap v4.0.0 (https://getbootstrap.com)
+ * Copyright 2011-2018 The Bootstrap Authors
+ * Copyright 2011-2018 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ */@import url("https://fonts.googleapis.com/css?family=Open+Sans:300italic,400italic,700italic,400,300,700");:root{--blue:#008cba;--indigo:#6610f2;--purple:#6f42c1;--pink:#e83e8c;--red:#F04124;--orange:#fd7e14;--yellow:#E99002;--green:#43ac6a;--teal:#20c997;--cyan:#5bc0de;--white:#fff;--gray:#888;--gray-dark:#333;--primary:#008cba;--secondary:#eee;--success:#43ac6a;--info:#5bc0de;--warning:#E99002;--danger:#F04124;--light:#eee;--dark:#222;--breakpoint-xs:0;--breakpoint-sm:576px;--breakpoint-md:768px;--breakpoint-lg:992px;--breakpoint-xl:1200px;--font-family-sans-serif:"Open Sans", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";--font-family-monospace:SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace}*,*::before,*::after{-webkit-box-sizing:border-box;box-sizing:border-box}html{font-family:sans-serif;line-height:1.15;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%;-ms-overflow-style:scrollbar;-webkit-tap-highlight-color:transparent}@-ms-viewport{width:device-width}article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}body{margin:0;font-family:"Open Sans", -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";font-size:0.9375rem;font-weight:400;line-height:1.5;color:#222;text-align:left;background-color:#fff}[tabindex="-1"]:focus{outline:0 !important}hr{-webkit-box-sizing:content-box;box-sizing:content-box;height:0;overflow:visible}h1,h2,h3,h4,h5,h6{margin-top:0;margin-bottom:0.5rem}p{margin-top:0;margin-bottom:1rem}abbr[title],abbr[data-original-title]{text-decoration:underline;-webkit-text-decoration:underline 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0}.nav{display:-webkit-box;display:-ms-flexbox;display:flex;-ms-flex-wrap:wrap;flex-wrap:wrap;padding-left:0;margin-bottom:0;list-style:none}.nav-link{display:block;padding:0.5rem 1rem}.nav-link:hover,.nav-link:focus{text-decoration:none}.nav-link.disabled{color:#ccc}.nav-tabs{border-bottom:1px solid rgba(0,0,0,0.1)}.nav-tabs .nav-item{margin-bottom:-1px}.nav-tabs .nav-link{border:1px solid transparent;border-top-left-radius:0;border-top-right-radius:0}.nav-tabs .nav-link:hover,.nav-tabs .nav-link:focus{border-color:rgba(0,0,0,0.1)}.nav-tabs .nav-link.disabled{color:#ccc;background-color:transparent;border-color:transparent}.nav-tabs .nav-link.active,.nav-tabs .nav-item.show .nav-link{color:#495057;background-color:#fff;border-color:rgba(0,0,0,0.1)}.nav-tabs .dropdown-menu{margin-top:-1px;border-top-left-radius:0;border-top-right-radius:0}.nav-pills .nav-link{border-radius:0}.nav-pills .nav-link.active,.nav-pills .show>.nav-link{color:#fff;background-color:#008cba}.nav-fill 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.dropdown-item:focus{background-color:#dc2c0f}.blockquote-footer{color:#888}table{font-size:0.8203125rem}.table-success,.table-info,.table-warning,.table-danger{color:#fff}.table-success,.table-success>th,.table-success>td{background-color:#43ac6a}.table-info,.table-info>th,.table-info>td{background-color:#5bc0de}.table-danger,.table-danger>th,.table-danger>td{background-color:#F04124}.table-warning,.table-warning>th,.table-warning>td{background-color:#E99002}.table-hover .table-success:hover,.table-hover .table-success:hover>th,.table-hover .table-success:hover>td{background-color:#3c9a5f}.table-hover .table-info:hover,.table-hover .table-info:hover>th,.table-hover .table-info:hover>td{background-color:#46b8da}.table-hover .table-danger:hover,.table-hover .table-danger:hover>th,.table-hover .table-danger:hover>td{background-color:#ea2f10}.table-hover .table-warning:hover,.table-hover .table-warning:hover>th,.table-hover .table-warning:hover>td{background-color:#d08002}label,.control-label,.help-block,.checkbox,.radio,.form-control-feedback{font-size:0.8203125rem}.dropdown-item{padding-top:0.75rem;padding-bottom:0.75rem;font-size:0.8203125rem;font-weight:300}.nav-tabs .nav-link,.nav-tabs .nav-link.disabled,.nav-tabs .nav-link.disabled:hover,.nav-tabs .nav-link.disabled:focus{border-color:rgba(0,0,0,0.1);background-color:#eee}.nav-tabs .nav-link:hover,.nav-tabs .nav-link:focus{background-color:#fbfbfb}.nav-pills .active{border:1px solid #0079a1}.breadcrumb{border:1px solid rgba(0,0,0,0.1);border-radius:3px;font-size:0.8203125rem;font-weight:300;text-transform:uppercase}.pagination{font-weight:300}.pagination .page-link{border-color:transparent;border-radius:3px;margin-left:0.1em;margin-right:0.1em}.pagination .page-link:hover,.pagination .page-link:focus{text-decoration:none}.pagination .page-item.disabled .page-link{border-color:transparent}.list-group{font-size:0.8203125rem;font-weight:300}.close{opacity:0.6;text-shadow:none}.close:hover,.close:focus{opacity:1}.alert{font-size:0.8203125rem;font-weight:300;color:#fff}.alert-primary,.alert-primary>th,.alert-primary>td{background-color:#008cba}.alert-secondary,.alert-secondary>th,.alert-secondary>td{background-color:#eee}.alert-success,.alert-success>th,.alert-success>td{background-color:#43ac6a}.alert-info,.alert-info>th,.alert-info>td{background-color:#5bc0de}.alert-danger,.alert-danger>th,.alert-danger>td{background-color:#F04124}.alert-warning,.alert-warning>th,.alert-warning>td{background-color:#E99002}.alert-dark,.alert-dark>th,.alert-dark>td{background-color:#222}.alert-light,.alert-light>th,.alert-light>td{background-color:#eee}.alert .alert-link{font-weight:normal;color:#fff;text-decoration:underline}.alert-secondary,.alert-secondary a:not(.btn),.alert-secondary .alert-link,.alert-light,.alert-light a:not(.btn),.alert-light .alert-link{color:#222}.badge{padding-bottom:.3em}.badge-warning,.badge-info{color:#fff}.progress[value]{height:22px;padding:2px;background-color:#f6f6f6;border:1px solid #ccc}
+
diff --git a/vizapp/www/style.css b/vizapp/www/style.css
index f625c9d..cd2a65d 100755
--- a/vizapp/www/style.css
+++ b/vizapp/www/style.css
@@ -1,3 +1,7 @@
+body {
+  /* Margin bottom by footer height */
+  margin-bottom: 60px;
+}
 label.radio { 
   padding-left: 18px;
   padding-right: 0px;
@@ -137,7 +141,7 @@ input[type="number"] {
   float: right;
 }
 
-div.busy {
+.busy {
   position:absolute;
   top: 40%;
   left: 50%;
@@ -146,9 +150,164 @@ div.busy {
   display:none;
   background: rgba(230, 230, 230, .8);
   text-align: center;
-  padding-top: 20px;
-  padding-left: 30px;
-  padding-bottom: 40px;
-  padding-right: 30px;
+  padding:20px 30px 40px 30px;
   border-radius: 5px;
+}
+
+.card{ 
+  max-height:100%;
+  display: flex;
+  padding-top:0;
+  flex-direction: column;
+  position:relative;
+  display:-webkit-box;
+  display:-ms-flexbox;
+  display:flex;
+  -webkit-box-orient:vertical;
+  -webkit-box-direction:normal;
+  -ms-flex-direction:column;
+  flex-direction:column;
+  min-width:0;
+  word-wrap:break-word;
+  background-color:#fff;
+  background-clip:border-box;
+  border:1px solid rgba(0,0,0,0.125);
+  border-radius:0
+}
+
+.card>hr{margin-right:0;margin-left:0}
+.card>.list-group:first-child .list-group-item:first-child{border-top-left-radius:0;border-top-right-radius:0}
+.card>.list-group:last-child .list-group-item:last-child{border-bottom-right-radius:0;border-bottom-left-radius:0}
+.card-body{-webkit-box-flex:1;-ms-flex:1 1 auto;flex:1 1 auto;padding:1.25rem}.card-title{margin-bottom:0.75rem}.card-subtitle{margin-top:-0.375rem;margin-bottom:0}.card-text:last-child{margin-bottom:0}
+.card-link:hover{text-decoration:none}
+.card-link+.card-link{margin-left:1.25rem}
+.card-header{padding:0.75rem 1.25rem;margin-bottom:0;background-color:rgba(0,0,0,0.03);border-bottom:1px solid rgba(0,0,0,0.125)}.card-header:first-child{border-radius:calc(0 - 1px) calc(0 - 1px) 0 0}
+.card-header+.list-group .list-group-item:first-child{border-top:0}
+.card-footer{ margin-top: auto;padding:0.75rem 1.25rem;background-color:rgba(0,0,0,0.03);border-top:1px solid rgba(0,0,0,0.125)}
+.card-footer:last-child{border-radius:0 0 calc(0 - 1px) calc(0 - 1px)}
+.card-header-tabs{margin-right:-0.625rem;margin-bottom:-0.75rem;margin-left:-0.625rem;border-bottom:0}
+.card-header-pills{margin-right:-0.625rem;margin-left:-0.625rem}
+.card-img-overlay{position:absolute;top:0;right:0;bottom:0;left:0;padding:1.25rem}
+.card-img{width:100%;border-radius:calc(0 - 1px)}
+.card-img-top{width:100%;border-top-left-radius:calc(0 - 1px);border-top-right-radius:calc(0 - 1px)}
+.card-img-bottom{width:100%;border-bottom-right-radius:calc(0 - 1px);border-bottom-left-radius:calc(0 - 1px)}
+.card-deck{display:-webkit-box;display:-ms-flexbox;display:flex;-webkit-box-orient:vertical;-webkit-box-direction:normal;-ms-flex-direction:column;flex-direction:column}
+.card-deck .card{margin-bottom:15px}
+@media (min-width: 760px){
+  .card{
+      height:600px;
+    }
+}
+@media (min-width: 900px){
+  .card{
+      height:500px;
+    }
+}
+@media (min-width: 1100px){
+  .card{
+      height:400px;
+    }
+}
+@media (min-width:1350px){
+   .card{
+      height:330px;
+    }
+}
+@media (min-width: 576px){
+  .card-deck{
+    -webkit-box-orient:horizontal;
+    -webkit-box-direction:normal;
+    -ms-flex-flow:row wrap;
+    flex-flow:row wrap;
+    margin-right:-15px;margin-left:-15px}
+    .card-deck .card{
+      display:-webkit-box;
+      display:-ms-flexbox;
+      display:flex;-webkit-box-flex:1;
+      -ms-flex:1 0 0;
+      flex:1 0 0;
+      -webkit-box-orient:vertical;
+      -webkit-box-direction:normal;
+      -ms-flex-direction:column;
+      flex-direction:column;
+      margin-right:15px;
+      margin-bottom:0;margin-left:15px
+    }
+}
+.card-group{
+  display:-webkit-box;
+  display:-ms-flexbox;
+  display:flex;-webkit-box-orient:vertical;
+  -webkit-box-direction:normal;
+  -ms-flex-direction:column;flex-direction:column
+  
+}
+  .card-group>.card{margin-bottom:15px}
+
+@media (min-width: 576px){
+  .card-group{-webkit-box-orient:horizontal;
+  -webkit-box-direction:normal;
+  -ms-flex-flow:row wrap;flex-flow:row wrap}
+  .card-group>.card{
+    -webkit-box-flex:1;
+    -ms-flex:1 0 0;
+    flex:1 0 0;margin-bottom:0
+  }
+  .card-group>.card+.card{
+    margin-left:0;border-left:0
+  }
+  .card-group>.card:first-child{
+    border-top-right-radius:0;border-bottom-right-radius:0}
+    .card-group>.card:first-child 
+    .card-img-top,.card-group>.card:first-child 
+    .card-header{border-top-right-radius:0}
+    .card-group>.card:first-child .card-img-bottom,.card-group>.card:first-child .card-footer{border-bottom-right-radius:0}
+    .card-group>.card:last-child{border-top-left-radius:0;border-bottom-left-radius:0}
+    .card-group>.card:last-child .card-img-top,.card-group>.card:last-child .card-header{border-top-left-radius:0}
+    .card-group>.card:last-child .card-img-bottom,.card-group>.card:last-child .card-footer{border-bottom-left-radius:0}
+    .card-group>.card:only-child{border-radius:0}
+    .card-group>.card:only-child .card-img-top,.card-group>.card:only-child .card-header{
+      border-top-left-radius:0;
+      border-top-right-radius:0
+    }
+    .card-group>.card:only-child .card-img-bottom,.card-group>.card:only-child .card-footer{
+      border-bottom-right-radius:0;
+      border-bottom-left-radius:0
+    }.card-group>.card:not(:first-child):not(:last-child):not(:only-child){border-radius:0}
+    .card-group>.card:not(:first-child):not(:last-child):not(:only-child) .card-img-top,.card-group>.card:not(:first-child):not(:last-child):not(:only-child) .card-img-bottom,.card-group>.card:not(:first-child):not(:last-child):not(:only-child) .card-header,.card-group>.card:not(:first-child):not(:last-child):not(:only-child) .card-footer{border-radius:0}
+}
+    .card-columns .card{margin-bottom:0.75rem}
+    
+    @media (min-width: 576px){
+      .card-columns{
+        -webkit-column-count:3;column-count:3;
+        -webkit-column-gap:1.25rem;column-gap:1.25rem}
+        .card-columns .card{display:inline-block;width:100%;}
+    }
+    
+.footer {
+      position: absolute;
+      bottom: 0;
+      width: 100%;
+      /* Set the fixed height of the footer here */
+      height: 60px;
+      line-height: 60px; /* Vertically center the text there */
+      background-color: #f5f5f5;
+}
+body > .container {
+  padding: 60px 15px 0;
+}
+
+.footer > .container {
+  padding-right: 15px;
+  padding-left: 15px;
+}
+    html {
+  position: relative;
+  min-height: 100%;
+}
+.centerbtn{
+  width: 130px;
+  text-align: center;
+  margin:0 auto;
 }
\ No newline at end of file
-- 
GitLab