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server.R
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server.R
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################################################################################################################
## Filename: server.r
## Created: October 09, 2015
## Author(s): Karsten Krug, Ozan Aygun
##
## Purpose: Shiny-app to perform differential expression analysis, primarily on proteomics data, to perform
## simple data QC, to interactively browse through the results and to download high-quality result
## figures.
##
## This file defines the server logical of the app. It also takes care of most of the user interface.
##
## Last updated January 18, 2023 by Natalie Clark (nclark@broadinstitute.org) - v 1.1.2
################################################################################################################
p_load(shiny)
############################################
## set maximum file size for upload
############################################
options(shiny.maxRequestSize = MAXSIZEMB*1024^2, stringsAsFactors=F)
###########################################################################################################
## Define server logic
############################################################################################
shinyServer(
function(input, output, session) {
hide(id = "loading-content", anim = TRUE, animType = "fade")
#####################################
## reactive variables to store
## data accross a session
#####################################
## error messages
error <- reactiveValues()
## test results
global.results <- reactiveValues(
## data tables
data=NULL,
table.norm=NULL,
table.log=NULL,
table.repro.filt=NULL,
filtered=NULL,
#export.results=F,
export.rmd=F,
export.xls=F,
export.gct=F,
export.results=F,
pca=NULL,
cm=NULL,
gprof=NULL,
repro.filt=NULL,
## ids and gene names
ids=NULL,
gene.names=NULL
)
## input data
global.input <- reactiveValues(
## meta data (gct 1.3)
rdesc=NULL,
cdesc=NULL
)
##################################################
## parameters
global.param <- reactiveValues(
file.done=F,
id.done=F,
grp.done=F, ## group assignment finished?
session.imported=F, ## flag whether this is an imported session
session.import.init=F, ## flag for initiate the session (used for to switch between default values for 'filter.value' and user=sepcified, i.e. after importing a session)
analysis.run=F, ## flag whether the analysis has been run
session.saved=F, ## flag whether session has been saved (v0.8.0.2)
file.gct3=F, ## GCT v1.3?
session=NULL, ## session id
user=NULL, ## user
grp=NULL, ## group to use for statistical testing
N.grp=NULL, ## number of defined groups for statistical testing
grp.norm = NULL, ## group to use for group-wise normalization
grp.colors=NULL, ## group color assignment
grp.colors.legend=NULL, ## group colors, names are group names
grp.colors.norm=NULL, ## group color assignment for normalization
grp.colors.legend.norm=NULL, ## group colors for normalization, names are group names
tabsep = '\t', ## default separator for non-gct files
tabsep.anno = '\t', ## default separator for non-gct files, used for annotation file
which.test='One-sample mod T', ## specify test
log.transform='none', ## log transformation
norm.data='none', ## data normalization
norm.per.group=FALSE, ## normalize per group?
filt.data='none', ## data filtering
##repro.filt='no', ## reproducibility filter
repro.filt.val=0.001,
##sd.filt='no', ## sd filter
sd.filt.val=10, ## remove lower 10 percent of features with lowest sd
na.filt.val=100, ## max. % missing values
filter.type='adj.p', ## default filter
filter.value=0.05, ## default filter value
run.test=0, ## number of times the 'Run analysis' button has been pressed during a user session
update.ppi.select= FALSE, ## trigger selectize, volcano
update.ppi.select.scat=FALSE, ## trigger selectize, scatterplot
collapse.ppi=TRUE, ## should PPI query panel be collapsed?
update.pca=FALSE,
update.cm=FALSE,
update.gprof.up=TRUE,
update.gprof.dn=TRUE
)
#####################################################
## plotting parameter
global.plotparam <- reactiveValues(
## multiscatter
ms.max=FALSE,
ms.min.val=-4,
ms.max.val=4,
ms.robustify=T,
## volcano
volc.ps=1.8, ## point size
volc.ls=1, ## label size
volc.grid=T, ## grid
volc.maxp=100, ## max. -log10 p-value
volc.hyper.fc=1, ## min. FC for hyperbolic curve
volc.hyper.curv=3, ## curvation parameter for hyperbol. curve
volc.label="ID_Symbol", #default text label
volc.init=T,
## heatmap
hm.cexCol=8,
hm.cexRow=3,
hm.scale="none",
hm.max=FALSE,
hm.max.val=4,
hm.show.rownames=T,
hm.show.colnames=T,
hm.clust="none",
## PCA
pca.x='PC 1',
pca.y='PC 2',
pca.z='PC 3',
## correlation matrix
cm.upper='pearson',
cm.lower='spearman',
cm.numb=FALSE,
## gprofiler
gprof.source.all=c('GO:BP', 'GO:MF', 'GO:CC', 'KEGG', 'WP'),
gprof.source.selected=c('GP:BP', 'KEGG'),
gprof.fdr=0.01,
## fanplot
HC.fan.show.tip.label=T,
HC.fan.tip.cex=1,
## profile plot
profile.plot.xlim='as-is' ## 'symmetric' or 'as-is'
)
## coordinates in volcano plot
volc <- reactiveValues()
volc.brush <- reactiveValues()
################################################################################
##
## instructions / help pages
##
################################################################################
callModule(printHTML, id='getting.started', what='gs', global.input = global.input, error=error)
callModule(printHTML, id='change.log', what='cl', global.input = global.input, error=error)
callModule(printHTML, id='id.column', what='id', global.param=global.param, global.input=global.input)
callModule(printHTML, id='gct3.file', what='gct3',global.param=global.param, global.input=global.input)
callModule(printHTML, id='exp.design', what='ed', global.param=global.param, global.input=global.input)
callModule(printHTML, id='analysis', what='ana', global.param=global.param, global.input=global.input)
#################################
## F5 hint
output$F5hint <- renderText({
HTML('<p align=\"center\"><font size=\"5\" color=\"red\">To analyze another data set or to start over, refresh this page.</font></p>' )
})
#####################################
## Error messages
output$error <- renderText({
if( is.null(error$msg) ) return()
if(is.null(error$title))
etitle <- 'Error'
else
etitle <- error$title
shinyalert(etitle, error$msg, type = "error", html=TRUE)
})
## #########################################################
## toggle all options for export
## #########################################################
observeEvent(input$export.toggle.all, {
updateCheckboxInput(session, "export.hm", "Heatmap", value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.box', 'Boxplots', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.volc', 'Volcano plot', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.phist', 'p-value histogram', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.pca', 'PCA', value=!input$export.toggle.all)
#updateCheckboxInput(session, 'export.pca.loadings', 'PCA loadings (xls)', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.ms', 'Multiscatter', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.excel', 'Excel sheet', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.gct.file', 'GCT files: 1) normalized data and 2) signed log p-values', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.cm', 'Correlation matrix', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.cb', 'Correlation boxplot', value=!input$export.toggle.all)
updateCheckboxInput(session, 'export.profile', 'Profile plot', value=!input$export.toggle.all)
})
## ########################################################
## session name
output$session.label <- renderMenu({
if(!global.param$session.saved) return()
label <- paste("Session:", global.param$label)
notificationItem(label, status='success', shiny::icon("folder", "fa-1x", lib='glyphicon'))
})
## ########################################################
## logged user
output$logged.user <- renderMenu({
if(is.null(session$user)) return()
user <- session$user
notificationItem(user, shiny::icon("user", "fa-1x", lib='glyphicon'), status='success')
})
## #########################################################
## logout user
output$logout <- renderMenu({
if(is.null(session$user)) return()
notificationItem('Logout', icon=shiny::icon("sign-out", "fa-1x"), status='success', href="__logout__")
})
################################################################################
##
## navbar - render UI
##
################################################################################
output$navbar <- renderUI({
if(!global.param$analysis.run) return()
##############################################
## determine the number of group comparisons,
## e.g. for the number of volcano plots to draw
##############################################
groups.comp <- unique(global.param$grp.comp)
## ##########################################
## class vector
grp <- global.param$grp
grp.norm <- global.param$grp.norm
grp.unique <- unique(grp)
################################################################################################################
##
## define the different tabs shown in the navigation bar
##
################################################################################################################
###############################################################
## EXPORT tab
## - export all figures/tables at once and generate a zip file
## - download the zip file
###############################################################
export.tab <- tabPanel('Export',
fluidRow(
column(width=6,
box(title="Session name",
fluidPage(
fluidRow(
HTML('Specify a name for the current session.')
),
fluidRow(
textInput( 'label', '', value=global.param$label, width=300)
),
fluidRow(
HTML('Save the current state of your session (SSPro).')
),
fluidRow(
actionButton('export.save.session', 'Save session')
)
),
status = "primary",
solidHeader = T,
width=NULL),
## ################################################
## action and download button for rmd, xls and zip
box(title="Export results",
fluidPage(
fluidRow(column(3, HTML('<a href="https://rmarkdown.rstudio.com/" target="_blank_">Markdown</a> report')),
column(3, HTML('Spreadsheet')),
column(3, HTML('GCT')),
column(3, HTML('Export all checked files'))),
fluidRow(column(3,
if(!global.results$export.rmd)
actionButton('export.rmd', 'html', icon = icon("code", lib="font-awesome"))
#actionButton('export.rmd', 'html', icon = icon("code", lib="font-awesome"), style="color: #000000; background-color: #ffa09b; border-color: #c7c9c7")
else
downloadButton('download.rmd', 'html', style="color: #00a805")
#downloadButton('download.rmd', 'html', style="color: #000000; background-color: #b7ff9b; border-color: #c7c9c7")
),
column(3,
if(!global.results$export.xls)
actionButton('export.xls', 'xlsx', icon = icon("table", lib="font-awesome"))
else
downloadButton('download.xls', 'xlsx', style="color: #00a805")
),
column(3,
if(!global.results$export.gct)
actionButton('export.gct', 'GCT', icon = icon("table", lib="font-awesome"))
else
downloadButton('download.gct', 'GCT', style="color: #00a805")
),
column(3, if(!global.results$export.results)
actionButton('export.results', 'zip', icon = icon("archive", lib="font-awesome"))
else
downloadButton('download.results', 'zip', style="color: #00a805"))
)),
status = "primary",
solidHeader = T,
width=NULL)#,
),
column(width=6,
box(title="Specify what to export:",
checkboxInput('export.toggle.all', 'Toggle all', value=F),
tags$hr(),
checkboxInput('export.hm', 'Heatmap',value=T),
checkboxInput('export.box', 'Boxplots',value=T),
checkboxInput('export.volc', 'Volcano plot',value=T),
checkboxInput('export.phist', 'p-value histogram',value=T),
checkboxInput('export.pca', 'PCA',value=T),
#checkboxInput('export.pca.loadings', "PCA loadings (xls)", value = T),
checkboxInput('export.ms', 'Multiscatter',value=T),
checkboxInput('export.excel', 'Excel sheet',value=T),
checkboxInput('export.gct.file', 'GCT files: 1) normalized data and 2) signed log p-values',value=T),
checkboxInput('export.cm', 'Correlation matrix',value=T),
checkboxInput('export.cb', 'Correlation boxplot',value=T),
checkboxInput('export.profile', 'Profile plot',value=T),
status = "primary",
solidHeader = T,
width=NULL
)
)
) # end fluidRow
) # end tabPanel
## ##########################################
## SUMMARY
## some general numbers on the
## uploaded data
##
## ##########################################
summary.tab <- tabPanel('Summary',
fluidRow(
box(title="Dataset:", solidHeader = T, status = "primary", width = 4,# color='purple',
tableOutput('summary.data')),
box(title="Workflow:", solidHeader = T, status = "primary",width = 4,
tableOutput('summary.workflow')),
box(title="Test results:", solidHeader = T, status = "primary",width = 4,
tableOutput('summary.test'))
),
fluidRow(
box(title="Quantified features", solidHeader = T, status = "primary",width = 12,
plotlyOutput('summary.nonmissing.data'))
),
fluidRow(
box(title="Missing values", solidHeader = T, status = "primary",width = 12,
plotlyOutput('summary.missing.data.row'))
),
fluidRow(
column(6,
box(title="Significant features (down-regulated)", solidHeader = T, status = "primary",width = 12,
plotOutput('summary.upset.dn'))
),
column(6,
box( title="Significant features (up-regulated)", solidHeader = T, status = "primary",width = 12,
plotOutput('summary.upset.up'))
)
)
) ## end tab panel
############################################
## gProfiler
gprof.tabs <- list()
gprof.tabs[[1]] <- 'Functional enrichment analysis'
for(i in 1:length( grp.unique )){
gprof.tabs[[i+1]] <- tabPanel(paste0( grp.unique[ i ] ),
fluidPage(
## ###############################
## plot
box( title=grp.unique[i], status = 'primary', solidHeader = T, width=12,
fluidRow(column(2, selectInput(paste0('gprof.src.', grp.unique[i]), label='Source' ,
choices=unlist(global.plotparam$gprof.source.all),
multiple = T,
selected = unlist(global.plotparam$gprof.source.selected )) ),
column(2, numericInput(paste0('gprof.fdr.', grp.unique[i]), label='FDR', value = global.plotparam$gprof.fdr, min = 0, max=1, step = 0.01)),
column(8)
),
fluidRow(
column(12, align='center', plotlyOutput( paste0('gprof.up.', grp.unique[i]) , width=800, height=600) )
), ## end fluiRow
fluidRow(
column(12, align='center', plotlyOutput( paste0('gprof.dn.', grp.unique[i]) , width=800, height=600) )
)
) ## end box
)
)
}
## ##########################################
## SCATTERPLOTS plotly
## - for each group comparison
##
## ##########################################
scat.tabs <- list()
scat.tabs[[1]] <- 'Scatterplots'
for(i in 1:length( grp.unique )){
## extract data columns of current experiment
grp.idx <- which(grp == grp.unique[i])
## index of other experiments
other.idx <- setdiff(1:length(grp), grp.idx)
grp.idx <- c(grp.idx, other.idx)
scat.x <- names(grp)[grp.idx]
scat.y <- names(grp)[grp.idx]
scat.tabs[[i+1]]=tabPanel(paste0( grp.unique[ i ] ),
fluidPage(
## ###############################
## select data columns to plot
box( title='Choose expression columns', status = 'primary', solidHeader = T, width=12,
fluidRow(
column(1),
#column(1, checkboxInput(paste0('scat.showall'), label='Show all columns', value=FALSE)),
column(5, selectInput( paste0('scat.x.', grp.unique[i]), 'x-axis', choices=scat.x, selected=scat.x[1], multiple=FALSE, selectize=TRUE)),
column(5, selectInput( paste0('scat.y.', grp.unique[i]), 'y-axis', choices=scat.y, selected=scat.y[2], multiple=FALSE, selectize=TRUE)),
column(1)
)
), # end box
## ###########################################################
## PPI stuff
box( title='Protein-protein interactions', status = 'primary', width=12, collapsible = TRUE, solidHeader=T, collapsed=global.param$collapse.ppi,
fluidRow(
column(3,
selectizeInput( inputId=gsub('\\.','', gsub('\\.', '', paste0('ppi.bait.scat.', grp.unique[i])) ), label=NULL,
choices=NULL,
selected=NULL,
options = list(
maxOptions=10,
placeholder='Protein/Gene'#,
#onInitialize = I('function() { this.setValue(""); }')
)
)
),
column(3, checkboxGroupInput(paste('ppi.db.scat', grp.unique[i], sep='.' ), 'Source data', choices=c('BioGRID (human)' = 'bg', 'InWeb' = 'iw', 'Reactome (human)' = 'react'), selected=c('bg') ))#,
#column(3, checkboxInput( paste('ppi.show.labels.scat', grp.unique[i], sep='.' ), 'Show labels', value=F) )
##column(1)
)),
## ###############################
## plot
box( title=grp.unique[i], status = 'primary', solidHeader = T, width=12,
fluidRow(
column(12, align='center', plotlyOutput( paste0('scatterplot.', grp.unique[i]) , width=800, height=600) )
) ## end fluiRow
) ## end box
) ## end fluidPage
) ## end tabPanel
} ## end for
## ##########################################
## VOLCANO
## tabs for the volcano plots
## NOT for F test
############################################
if( !(global.param$which.test %in% c('mod F', 'none'))) {
volc.tabs <- list()
volc.tabs[[1]] <- 'Volcanos'
for(i in 1:length(unique(groups.comp))){
volc.tabs[[i+1]]=tabPanel(paste0( groups.comp[i] ),
fluidPage(
## ###########################################################
## volcano plotting parameters
box( title='Plotting parameters', status = 'primary', solidHeader = T, width=12,
fluidRow(
column(2, numericInput( paste("cex.volcano",groups.comp[i], sep='.'), "Point size", value=global.plotparam$volc.ps, min=1, step=1, width='100px')),
##column(1, numericInput( paste("opac.volcano",groups.comp[i],sep='.'), "Opacity %", value=50, min=0, max=100, step=10)),
column(2, numericInput( paste("cex.volcano.lab",groups.comp[i],sep='.'), "Label size", value=global.plotparam$volc.ls, min=.1, step=.1, width='100px')),
column(2, selectInput( paste("grid.volcano",groups.comp[i],sep='.'), "Grid", c(T, F), selected=global.plotparam$volc.grid, width='100px')),
column(2, numericInput( paste( "max.logP", groups.comp[i], sep='.'), "Max. Log10(p-value)", value=global.plotparam$volc.maxp, min=20, max=300, step=10, width='100px') ),
column(2, selectInput( paste("volc.label",groups.comp[i],sep='.'), "Labels", c("ID_Symbol", "ID","Symbol"), selected=global.plotparam$volc.label, width='100px'))
##column(1, downloadButton(paste('downloadVolcano', groups.comp[i],sep='.'), 'Download (pdf)'))
)
),
## ###########################################################
## PPI stuff
box( title='Protein-protein interactions', status = 'primary', width=12, collapsible = TRUE, solidHeader=T, collapsed=global.param$collapse.ppi,
fluidRow(
column(3,
selectizeInput( inputId=gsub('\\.','', gsub('\\.', '', paste0('ppi.bait.', groups.comp[i])) ),
label=NULL,
choices=NULL,
selected=NULL,
multiple=F,
options = list(
maxOptions=10,
placeholder='Protein/Gene'#,
#oninit = I('function() { this.setValue(" "); }')
#onInitialize = I('function() { this.setValue("Testtststs"); }')
)
)
),
column(3, checkboxGroupInput(paste('ppi.db', groups.comp[i], sep='.' ), 'Source data', choices=c('BioGRID (human)' = 'bg', 'InWeb' = 'iw', 'Reactome (human)' = 'react'), selected=c('bg') )),
column(3, checkboxInput( paste('ppi.show.labels', groups.comp[i], sep='.' ), 'Show labels', value=F) ),
column(1, checkboxInput( paste('ppi.hyper.filt', groups.comp[i], sep='.' ), 'Hyperbolic curve', value=F)),
column(1, numericInput(paste( "ppi.min.fc", groups.comp[i], sep='.'), 'Min. FC', value=global.plotparam$volc.hyper.fc, min=0, max=100, step=0.1)),
column(1, numericInput(paste( "ppi.curve", groups.comp[i], sep='.'), 'Curvation', value=global.plotparam$volc.hyper.fc, min=0.1, max=100, step=0.1) )
##column(1)
)),
## ############################################################
## the actual plot plus table
fluidRow(
## plot
column(width=7,
box( width=NULL, title='Volcano plot', status = 'primary', solidHeader = T,
plotOutput( paste("volcano", groups.comp[i], sep='.'), height=600, click=paste('plot_click', groups.comp[i], sep='.'), hover=hoverOpts(id=paste('plot_hover', groups.comp[i], sep='.'), delay=10), brush=brushOpts(id=paste('plot_brush', groups.comp[i], sep='.'), resetOnNew=T, delayType='debounce', delay='1000' ), dblclick=paste('plot_dblclick', groups.comp[i], sep='.'))
)),
## table
column(width=5,
box(width=NULL, title='Selection', status = 'primary', solidHeader = T,
fluidRow(
column(6, actionButton(inputId=paste('volc.tab.reset', groups.comp[i], sep='.'), label='Remove all')),
column(6, actionButton(inputId=paste('volc.tab.reset.select', groups.comp[i], sep='.'), label='Remove selected'))
),
tags$hr(),
dataTableOutput(paste('volc.tab.selected', groups.comp[i], sep='.'))
)))
) ## end fluidPage
) ## end tabPanel
} ## end for i
} # end if
################################################
##
## clustering
##
## #############################################
############################################
## HEATMAP
############################################
hm.tab <- tabPanel('Static heatmap',
box(title='Static Heatmap', status = 'primary', solidHeader = T, width="100%", height="100%",
fluidRow(
column(2, numericInput( "cexCol", "Font size column", value=ifelse( !is.null(global.plotparam$hm.cexCol), global.plotparam$hm.cexCol, 12 ), min=1, step=1)),
column(2, numericInput( "cexRow", "Font size row", value=ifelse( !is.null(global.plotparam$hm.cexRow), global.plotparam$hm.cexRow, 6), min=1, step=1)),
column(2, selectInput( "hm.scale", "Scale", c("row","column","none"), selected=global.plotparam$hm.scale)),
column(2, selectInput( "hm.clust", "Cluster", c("column","row","both","none"), selected=ifelse(global.param$which.test != "mod F", "none" ,"both"))),
column(2, checkboxInput('hm.max', 'Cap values', value=global.plotparam$hm.max)),
column(2, numericInput( "hm.max.val", "Max. value", value=global.plotparam$hm.max.val, step=1, min=2))
),
fluidRow(
column(2, checkboxInput('hm.show.colnames', 'Show column labels', value=global.plotparam$hm.show.colnames)),
column(2, checkboxInput('hm.show.rownames', 'Show row labels', value=global.plotparam$hm.show.rownames)),
column(8)
),
fluidRow(
column(12, align='center', plotOutput("HM", height=min( dynamicHeightHM( nrow(global.results$filtered)), 1200 ), width=dynamicWidthHM(length(global.param$grp))) )
)
)
)
## ###########################################
## HEATMAPPLY
## ###########################################
# hm.int.tab <- tabPanel('Interactive heatmap',
# box(title='Interactive Heatmap', status = 'primary', solidHeader = T, width="100%", height="100%",
# fluidRow(
# column(2, selectInput( "hm.int.scale", "Scale", c("row","column","none"), selected=global.plotparam$hm.scale)),
# column(2, selectInput( "hm.int.clust", "Cluster", c("column","row","both","none"), selected=ifelse(global.param$which.test != "mod F", "none" ,"both"))),
# column(2, checkboxInput('hm.int.max', 'Cap values', value=global.plotparam$hm.max)),
# column(2, numericInput( "hm.int.max.val", "Max. value", value=global.plotparam$hm.max.val, step=1, min=2))
# ),
# fluidRow(
# column(12, align='center', plotlyOutput("HM.int", height=1000, width=1000 ))
# )
# )
# )
#
## #############################################
## FANPLOT
## #############################################
hc.fanplot <- tabPanel('Fanplot',
box(title='Fanplot', status = 'primary', solidHeader = T, width="100%", height="100%",
fluidRow(
column(1, checkboxInput('HC.fan.show.tip.label', label = 'Show names', value = global.plotparam$HC.fan.show.tip.label)),
column(2, numericInput('HC.fan.tip.cex', label = 'Label size', value = global.plotparam$HC.fan.tip.cex, min = 0.1, max=10, step = 0.2, width = '40%')),
column(9)
),
fluidRow(
column(12, align='center', plotOutput("HC.fan", height = 600, width=1200 ))
)
)
)
clust.tab <- vector('list', 2)
clust.tab[[1]] <- hm.tab
#clust.tab[[2]] <- hm.int.tab
#clust.tab[[3]] <- hc.fanplot
clust.tab[[2]] <- hc.fanplot
## ##############################################
## MORPHEUS widget
##
## ##############################################
# morph.tab <- tabPanel('Morpheus',
# box(title='Morpheus', status = 'primary', solidHeader = T, width="100%", height="100%",
# fluidRow(
#
# column(12, morpheusOutput(outputId = "HM.morpheus"#,
# #height=min( dynamicHeightHM( nrow(global.results$filtered)), 1200 ),
# #width=dynamicWidthHM(length(global.param$grp))
# )
# )
# )
# )
# )
#
#
#############################################
##
## PCA
##
#############################################
pca.tab2 <- list()
## ##################################################
## Run PCA
## ##################################################
pca.tab2[[1]] <- tabPanel('Explained variance',
fluidRow(
box(title='Summary', status='primary', solidHeader = T, htmlOutput('run.pca')),
box(title='Variance', status='primary', solidHeader = T, plotOutput('pca.var'))
)
)
## ##################################################
## PC plots
## ##################################################
if(global.param$file.gct3){ ## CGT v1.3 - the user can user different annotations to color the plots
pca.tab2[[2]] <- tabPanel('PC plots',
fluidPage(
fluidRow(
box( title = 'Select principle components', status='primary', solidHeader = T, align='center',
column(width=4, selectInput('pca.x', 'x-axis', paste('PC', 1:10)), selected=global.plotparam$pca.x),
column(width=4, selectInput('pca.y', 'y-axis', paste('PC', 1:10), selected=global.plotparam$pca.y)),
column(width=4, selectInput('pca.z', 'z-axis', paste('PC', 1:10), selected=global.plotparam$pca.z))
),
box(title='Select annotation', status='primary', solidHeader = T, align='center',
column(6, selectInput('pca.grp.col', label = 'Color by', choices = colnames(global.input$cdesc), selected = global.plotparam$pca.grp.col),
column(6),
)
)
),
fluidRow(
box( title='2D', status = 'primary', solidHeader = T, width = 1000, height = 700,
column(12, align='center', plotlyOutput("pcaxy.plotly", width=800, height=600))
)
),
fluidRow(
box( title='3D', status = 'primary', solidHeader = T, width = 800, height = 900,
column(12, align='center', plotlyOutput("pcaxyz.plotly", width=800, height=800))
)
)
)
)
} else { ## no GCT v1.3
pca.tab2[[2]] <- tabPanel('PC plots',
fluidPage(
fluidRow(
box( title = 'Select principle components', status='primary', solidHeader = T, align='center',
column(width=4, selectInput('pca.x', 'x-axis', paste('PC', 1:10)), selected=global.plotparam$pca.x),
column(width=4, selectInput('pca.y', 'y-axis', paste('PC', 1:10), selected=global.plotparam$pca.y)),
column(width=4, selectInput('pca.z', 'z-axis', paste('PC', 1:10), selected=global.plotparam$pca.z))
)
),
fluidRow(
box( title='2D', status = 'primary', solidHeader = T, width = 1000, height = 700,
column(12, align='center', plotlyOutput("pcaxy.plotly", width=800, height=600))
)
),
fluidRow(
box( title='3D', status = 'primary', solidHeader = T, width = 800, height = 900,
column(12, align='center', plotlyOutput("pcaxyz.plotly", width=800, height=800))
)
)
)
)
}
## ####################################################################
## Loadings plot
## ####################################################################
#pca.tab2[[3]] <- tabPanel('Loadings',
# fluidPage(
# fluidRow(
# column(width=12,
# box(title='Loadings by Ozan Aygun', solidHeader=T, status='primary', width=1000,## height=min( nrow(global.results$filtered), global.plotparam$pca.load.topn )*20+50,
# sliderInput("pca.load.topn", "Choose number of loadings", 1, 100, 20),
# ## plotOutput("pca.loadings")##, width=1000, height=min(nrow(global.results$filtered), global.plotparam$pca.load.topn )*20 )
# ## ),
# ## box(title = "PCA loadings scatterplots",solidHeader = T, status = 'primary',width = 1000,
# background = "navy",
# plotOutput("scatter.pca.loadings")
# ))
#
# )
# )
#)
## ###########################################
## TABLE: filtered result table
##
## ###########################################
table.tab <- tabPanel('Table',
fluidPage(
fluidRow(column(12, dataTableOutput("tableprev")))
)
)
#############################################
## QC tabs
##
#############################################
qc.tabs <- vector('list', 5)
##names(qc.tabs) <- c('Boxplots', 'p-values', 'Multi scatter', 'Correlation matrix', 'Correlation matrix transposed')
###########################
## boxplots
##qc.tabs[['Boxplots']] <- tabPanel('Boxplots',
qc.tabs[[1]] <- tabPanel('Boxplots',
fluidPage(
fluidRow(
box(title="Before normalization", solidHeader=T, status="primary",
column(width=12, plotOutput("expr.boxplot", width="100%", height=max( 30*(ncol( global.input$table)+2), 500)))
),
if(!is.null(global.results$table.norm)){
box(title="After normalization", solidHeader=T, status="primary",
column(width=12, plotOutput("expr.boxplot.norm", width="100%", height=max( 30*(ncol( global.input$table)+2), 500)))
)
}
)
)
)
###########################
## profile plots
##qc.tabs[['Profile plots']] <- tabPanel('Profile plots',
qc.tabs[[2]] <- tabPanel('Profile plots',
if(is.null(global.results$table.norm)){
fluidPage(
fluidRow(
box(title='Data range', solidHeader=T, status='primary',
column(width=6, selectInput('profile.plot.xlim', label='x-axis', choices=c('symmetric', 'as-is'), selected = global.plotparam$profile.plot.xlim))
)
),
fluidRow(
box(title="Before normalization", solidHeader=T, status="primary",
column(width=12, plotlyOutput("expr.profile"))
))
)
} else {
fluidPage(
fluidRow(
box(title='Data range', solidHeader=T, status='primary',
column(width=6, selectInput('profile.plot.xlim', label='x-axis', choices=c('symmetric', 'as-is'), selected = global.plotparam$profile.plot.xlim))
)
),
fluidRow(
box(title="Before normalization", solidHeader=T, status="primary",
column(width=12, plotlyOutput("expr.profile"))
),
box(title="After normalization", solidHeader=T, status="primary",
column(width=12, plotlyOutput("expr.profile.norm"))
)
)
)
}
)
###########################
## P-value distribution
##qc.tabs[['P-values']] <- tabPanel('P-values',
qc.tabs[[3]] <- tabPanel('p-values',
fluidPage(
fluidRow(
box(title="Distribution of p-values", solidHeader=T, status="primary", width=1000, height=600*ifelse( global.param$which.test != 'mod F', length(unique(global.param$grp.comp)), 1 ),
column(12, plotOutput("pval.hist"))
)
)
)
)
############################
## correlation multiscatter
##qc.tabs[['Multi scatter']] <- tabPanel('Multi scatter',
qc.tabs[[4]] <- tabPanel('Multi scatter',
fluidPage(
fluidRow(
box(title="Parameters", solidHeader=T, status="primary", width='100%',
column(4, checkboxInput('ms.robustify', 'Robust scale (99.99 % of data)', value=global.plotparam$ms.robustify)),
column(1, checkboxInput('ms.max', 'Define limits', value=global.plotparam$ms.max)),
column(2, numericInput( "ms.min.val", "min.", value=global.plotparam$ms.min.val, step=1)),
column(2, numericInput( "ms.max.val", "max.", value=global.plotparam$ms.max.val, step=1)),
column(3, actionButton('ms.update',label = 'Update plot'))
)
),
fluidRow(
box(title='Multiscatter', solidHeader=T, status="primary", width=100*(ncol(data.frame(global.input$table))-1), height=130*(ncol(data.frame(global.input$table)) - 1),
column(12, plotOutput("multi.scatter"))
)
)
)
)
###########################
## correlation matrix
## qc.tabs[['Correlation matrix']] <- tabPanel('Correlation matrix',
qc.tabs[[5]] <- tabPanel('Correlation matrix',
fluidPage(
fluidRow(
box(title='Parameters', solidHeader=T, status="primary",
column(3, selectInput( "cm.upper", "Upper triangle", c("pearson","spearman","kendall"), selected=global.plotparam$cm.upper)),
column(3, selectInput( "cm.lower", "Lower triangle", c("pearson","spearman","kendall"), selected=global.plotparam$cm.lower)),
column(1, checkboxInput('cm.numb', 'Show numbers', value=global.plotparam$cm.numb)),
column(5))
),
fluidRow(
box(title='Correlation matrix', solidHeader=T, status="primary", width=dynamicWidthHM( length(global.param$grp) ), height=dynamicWidthHM( length(global.param$grp) ),
column(12, plotOutput("correlation.matrix", 800, 800))
)
)
)
)
##############################
## correlation boxplots
qc.tabs[[6]] <- tabPanel('Correlation boxplots',
fluidPage(
fluidRow(
box(title='Correlation boxplots', solidHeader=T, status="primary", width=1000, height=800,
column(12, plotOutput("corr.box.group", 800, 600))
)
)
)
)
## #################################################################################
##
## insert the tabs
##
## #################################################################################
if( !(global.param$which.test %in% c('mod F', 'none'))){
navbarPage(title='', id='mainPage',
#######################################
## insert summary tab
#######################################
summary.tab,
#######################################
## insert heatmap
#######################################
##hm.tab,
# navbarMenu('Clustering', clust.tab[[1]], clust.tab[[2]], clust.tab[[3]]),
navbarMenu('Clustering', clust.tab[[1]], clust.tab[[2]]),
##do.call(navbarMenu, hm.tab),
#######################################
## insert volcanos
#######################################
#if( !(global.param$which.test %in% c('mod F', 'none'))){
do.call(navbarMenu, volc.tabs),
# } else {
# list()
# },
#morph.tab,
## ####################################