inst/app/www/R/analysis_tabUI.R
In william0701/CeNetOmnibus: A Shiny based application for ceRNA network construction and analysis.
create_property_checkboxgroup=function(type,id,label,items,f)
{
selection=list()
for(i in items)
{
s=div(class="btn-group btn-goup-toggle",
tags$button(class="btn checkbtn btn-primary",type=type,
tags$span(class="check-btn-icon-yes",tags$i(class='glyphicon glyphicon-ok')),
tags$span(class="check-btn-icon-no"),
tags$input(type='checkbox',autocomplete="off",name=paste(type,"_centrality",sep=""),value=i,HTML(i),onchange=paste(f,"(this)",sep=""))
)
)
selection=c(selection,list(s))
}
ui=div(class='form-group shiny-input-container shiny-input-container-inline',
tags$label(class='control-label',HTML(label)),
tags$br(),
div(id=id,class='checkboxGroupButtons shiny-bound-input',
div(class='btn-group btn-group-container-sw',"data-toggle"="buttons","aria-label"="...",
selection
)
)
)
return(ui)
}
network_property_panel=tabPanel(title="Network Topology Properties",
h2("Part1: Network Topology Properties",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class="box-header",
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class='btn btn-box-tool',"data-widget"="collapse",
tags$i(class='fa fa-minus')
)
)
),
div(class="box-body",
create_property_checkboxgroup(type='node',id='node_centrality',label='Nodes Centrality',
items=c("Degree","Betweenness","Closeness",'Clustering Coefficient'),f='showNodeCentrality'),
create_property_checkboxgroup(type='edge',id='edge_centrality',label='Edges Centrality',items=c("Betweenness"),f='showEdgeCentrality'),
tags$br(),
div(id="network_property",class="row")
),
div(class='box-footer',
div(class='pull-right',
downloadButton(outputId='export_network_node_property', label = "Export Node Property"),
downloadButton(outputId='export_network_edge_property', label = "Export Edge Property"),
downloadButton(outputId='export_network_property_plot', label = "Export Plots")
)
)
)
)
network_module_panel=tabPanel(title="Network Modules",
h2("Part2: Network Modules",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class='box-header',
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class='btn btn-box-tool',"data-widget"="collapse",
tags$i(class='fa fa-minus')
)
)
),
div(class='box-body',
div(class="row",
div(class="col-lg-4 col-xs-6",
pickerInput(inputId = 'community_algorithm',label = 'Community Detection Algorithm',
choices = c("NG Algorithm"="cluster_edge_betweenness",
"Modularity Optimization"="cluster_fast_greedy",
"Label Propagation"="cluster_label_prop",
"Louvain Method"="cluster_louvain",
"Maximal Modularity"="cluster_optimal",
"Random Walk"="cluster_walktrap",
"InfoMap"="cluster_infomap",
"Cograph Community"="cluster_cograph",
"Markov Clustering"="cluster_mcl",
"Linkcomm"="cluster_linkcomm",
"MCODE"="cluster_mcode"
),
width = "100%"
)
),
div(class="col-lg-3 col-xs-6",style="padding:0;margin:0",
div(class="form-group shiny-input-container",
tags$label(class="control-label",HTML(" ")),
div(class="btn-group",style="display:table-row",
#tags$label(class="control-label"),tags$br(),
tags$button(id="community_para_check",class="btn btn-warning",HTML("Choose Parameter"),onclick="run_parameter_choose(this)"),
tags$button(id="community_detection",class="btn btn-primary",HTML("Perform"),onclick="run_community_detection(this)"
)
)
)
)
),
div(class="row",
div(class="col-lg-12",
conditionalPanel("input.community_algorithm=='cluster_edge_betweenness'"),
conditionalPanel("input.community_algorithm=='cluster_fast_greedy'"),
conditionalPanel("input.community_algorithm=='cluster_label_prop'"),
conditionalPanel("input.community_algorithm=='cluster_louvain'"),
conditionalPanel("input.community_algorithm=='cluster_optimal'"),
conditionalPanel("input.community_algorithm=='cluster_walktrap'",
div(class="col-lg-4",style="padding-left:0",
numericInput(inputId="walktrap_step",label = "Steps",value = 4,min=1,max=NA,step = 1,width = "100%")
)
),
conditionalPanel("input.community_algorithm=='cluster_infomap'",
div(class="col-lg-4",style="padding-left:0",
numericInput(inputId="infomap_nb_trails",label = "Module Counts",value = 10,min=2,max=NA,step = 1)
)
),
conditionalPanel("input.community_algorithm=='cluster_cograph'"),
conditionalPanel("input.community_algorithm=='cluster_mcl'",
div(class='row',
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_expansion",label = "Expansion",value = 2,min = 1,max = Inf,step = 0.1,width = "100%")
),
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_inflation",label = "Inflation",value = 2,min = 1,max = Inf,step = 0.1,width = "100%")
),
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_max_iter",label = "Maximal Iteration",value = 100,min = 1,max = Inf,step = 1,width = "100%")
)
)
),
conditionalPanel("input.community_algorithm=='cluster_linkcomm'",
div(class='row',
div(class='col-lg-4',
pickerInput(inputId = "linkcomm_hcmethod",label = "Hierarchical Clustering Method ",
choices = c("average"="average",'ward'='ward','single'='single','complete'='complete','mcquitty'='mcquitty','median'='median','centroid'='centroid'),
selected='average',width="100%"
)
)
)
),
conditionalPanel("input.community_algorithm=='cluster_mcode'",
div(class="row",
div(class="col-lg-2",
numericInput(inputId='mcode_vwp',label = "Vertex Weight Percentage",value = 0.5,min = 0,max = 1,step = 0.1,width = '100%')
),
div(class="col-lg-2",
div(class='form-group shiny-input-container',
tags$label(HTML("Haircut")),
switchInput(inputId='mcode_haircut',value = F,onLabel = 'True',offLabel = "False")
)
)
),
div(class="row",
div(class="col-lg-2",
div(class='form-group shiny-input-container',
tags$label(HTML("Fluff")),
switchInput(inputId='mcode_fluff',value = F,onLabel = 'True',offLabel = "False")
)
)
# conditionalPanel("input.mcode_fluff",
# div(class="col-lg-2",
# numericInput(inputId='mcode_fdt',label = "Cluster Density Cutoff",value = 0.8,min = 0,max = 1,step = 0.1,width = '100%')
# )
# )
)
),
tags$br()
)
),
div(class="row",
div(class="col-lg-12",
tags$label(HTML("Module Summary"),downloadButton(outputId = "export_module_info",label = "Export")),
div(id="module_info_box")
)
),
div(class='row',
div(class="col-lg-12",
tags$label(HTML("Module Visualization")),
div(id="module_visualization",class='row')
)
)
),
div(class='box-footer',
conditionalPanel('input.community_algorithm=="cluster_edge_betweenness"',
tags$cite(class="bg-orange-active",HTML("* Newman M E J, Girvan M. Finding and evaluating community structure in networks[J]. Physical review E, 2004, 69(2): 026113."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_fast_greedy"',
tags$cite(class="bg-orange-active",HTML("* Clauset A, Newman M E J, Moore C. Finding community structure in very large networks[J]. Physical review E, 2004, 70(6): 066111."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_label_prop"',
tags$cite(class="bg-orange-active",HTML("* Raghavan U N, Albert R, Kumara S. Near linear time algorithm to detect community structures in large-scale networks[J]. Physical review E, 2007, 76(3): 036106.",style="font-weight:bold"))
),
conditionalPanel('input.community_algorithm=="cluster_louvain"',
tags$cite(class="bg-orange-active",HTML("* Blondel V D, Guillaume J L, Lambiotte R, et al. Fast unfolding of communities in large networks[J]. Journal of statistical mechanics: theory and experiment, 2008, 2008(10): P10008."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_optimal"',
tags$cite(class="bg-orange-active",HTML("* Brandes U, Delling D, Gaertler M, et al. On modularity clustering[J]. IEEE transactions on knowledge and data engineering, 2007, 20(2): 172-188."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_walktrap"',
tags$cite(class="bg-orange-active",HTML("* Pons P, Latapy M. Computing communities in large networks using random walks[C]//International symposium on computer and information sciences. Springer, Berlin, Heidelberg, 2005: 284-293."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_infomap"',
tags$cite(class="bg-orange-active",HTML("* Rosvall M, Bergstrom C T. Maps of information flow reveal community structure in complex networks[J]. arXiv preprint physics.soc-ph/0707.0609, 2007."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_cograph"',
tags$cite(class="bg-orange-active",HTML("* Jia S, Gao L, Gao Y, et al. Defining and identifying cograph communities in complex networks[J]. New Journal of Physics, 2015, 17(1): 013044."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_mcl"',
tags$cite(class="bg-orange-active",HTML("* Stijn van Dongen, Graph Clustering by Flow Simulation. PhD thesis, University of Utrecht, May 2000."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_linkcomm"',
tags$cite(class="bg-orange-active",HTML("* Ahn Y Y, Bagrow J P, Lehmann S. Link communities reveal multiscale complexity in networks[J]. nature, 2010, 466(7307): 761."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_mcode"',
tags$cite(class="bg-orange-active",HTML("* Bader G D, Hogue C W V. An automated method for finding molecular complexes in large protein interaction networks[J]. BMC bioinformatics, 2003, 4(1): 2."),style="font-weight:bold")
)
)
),
div(id="community_table")
)
enrichment_panel=tabPanel(title="Enrichment Analysis",
h2("Part3: Enrichment Analysis",style='font-family:Georgia'),
fluidRow(
box(width = 7,
title = "Select parameters",collapsible = T,collapsed = F,status = 'primary',solidHeader=T,
footer=tags$button(id="enrichment_finish",class="btn btn-primary btn-flat action-button shiny-bound-input",
HTML("Perform"),onclick="run_enrichment_finish(this)"),
div(class='row',
div(class='col-lg-6',
prettyRadioButtons(
inputId = "gProfileOnline_Or_custom_analysis",
label = "Enrichment Source",
choices = c("g:Profile (Online)"="gProfile", "Custom Input"="custom_input"),
inline = TRUE
)
),
conditionalPanel("input.gProfileOnline_Or_custom_analysis=='gProfile'",
div(class='col-lg-6',
pickerInput(inputId = 'Organism_enrichment',label = 'Organism:',
choices = c(),
options = list(size = 8,`live-search` = TRUE),
width = "100%"
)
),
div(class="col-lg-12",
pickerInput(inputId = 'enrichment_Data_Sources',label = 'Data Sources',
choices = c("GO Molecular Function(MF)"="GO:MF",
"GO Cellular Component(CC)"="GO:CC",
"GO Biological Process(BP)"="GO:BP",
"KEGG"="KEGG",
"Reactome"="REAC",
"WikiPathways"="WP"
),
multiple = TRUE,
options = list("actions-box"=T)
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Significance_threshold',label = 'Significance threshold',
choices = c("Benjamini-Hochberg FDR"="fdr","g:SCS threshold"="g_SCS","Bonferroni Correction"="bonferroni")
)
)
),
conditionalPanel("input.gProfileOnline_Or_custom_analysis=='custom_input'",
div(class='col-lg-10',
fileInput(inputId="enrichment_Custom_input_function_gene",label = "Custom input function gene")
),
div(class="col-lg-2",style="padding-left:0px;padding-top:5px;margin:0",
div(class="form-group shiny-input-container",
div(class="input-group-btn"),tags$br(),
tags$button(id="show_custom_input_file",class="btn btn-primary btn-flat action-button shiny-bound-input",
HTML("Preview"),onclick="run_show_custom_input_file(this)")
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Significance_threshold_custom',label = 'Significance threshold',
choices = c("Original P-value"="","Benjamini-Hochberg FDR"="fdr","Bonferroni Correction"="bonferroni")
)
)
),
div(class='col-lg-6',
numericInput(inputId = "enrichment_User_threshold", label = "User threshold", value = 0.05,min = 0,max = 1,step = 0.01)
)
),
div(class='row',
div(class='col-lg-6',
prettyRadioButtons(
inputId = "choose_which_gene_to_analysis",
label = "Gene Set Source",
choices = c("Modules Gene"="Modules_Gene", "Custom Gene"="Custom_Gene"),
inline = TRUE
)
),
conditionalPanel("input.choose_which_gene_to_analysis=='Modules_Gene'",
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Module_analysis1',label = 'Module analysis',
choices = c(),
multiple = TRUE,
options = list(size = 8,`live-search` = TRUE,"actions-box"=T),
width = "100%"
)
)
),
conditionalPanel("input.choose_which_gene_to_analysis=='Custom_Gene'",
div(class='col-lg-12',
textAreaInput(inputId="custom_input_gene",label = "Custom input gene",
value ="",placeholder = "Please input gene set, one gene per line...",
height = "100px")
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Numeric_IDs_treated_as',label = 'Gene ID Map',
choices = c(),
options = list(size = 8,`live-search` = TRUE)
)
),
div(class="col-lg-6",
prettyRadioButtons(
inputId = "enrichment_choose_show",
label = "Plot Type",
choices = c("Bar Plot"="bar_plot", "Point Plot"="point_plot"),
inline = TRUE
)
)
)
),
box(width = 5,
title = "Custom Gene Preview",collapsible = T,collapsed = F,status = 'primary',solidHeader=T,
formattableOutput('custom_preview_panel',width = '30%')
)
),
div(id="all_enrichment_show")
)
survival_panel=tabPanel(title="Survival Analysis",
h2("Part4: Survival Analysis",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class="box-header",
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class="btn btn-box-tool","data-widget"="collapse",
tags$i(class="fa fa-minus")
)
)
),
div(class="box-body",
tabsetPanel(type="tabs",
tabPanel(title="Parameter",
div(class="col-lg-4",style="padding:0px",
tags$fieldset(
tags$legend(HTML("Clinical Information")),
div(class='col-lg-6',style="padding:0px",
tags$button(class="btn bg-navy btn-block btn-flat",
onclick="demo_clinical()",
tags$i(class='fa fa-upload'),
HTML("Upload Demo Data")
)),
div(class="col-lg-12",style="padding:0px",
fileInput(inputId="clinical_file",label = "Clinical Data")
),
div(class='col-lg-12',style="padding:0px",
prettyRadioButtons(inputId = 'clinical_seperator',label = 'Seprator',choices = c("Tab"="\t",'Comma'=',','Space'=' ','Semicolon'=';'),status='primary',inline=T)
),
div(class="col-lg-12",style="padding:0px",
prettyRadioButtons(inputId = 'clinical_header',label = 'Header',choices = c("With header"=T,'Without header'=F),selected=T,status='primary',inline=T)
),
div(class="col-lg-12",style="padding:0px",
prettyRadioButtons(inputId = 'clinical_first_col',label = 'First Column For Row Name?',choices = c("Yes"=T,'No'=F),selected=F,status='primary',inline=T)
)
)
),
div(class="col-lg-5",
tags$fieldset(
tags$legend(HTML("Expression Data")),
div(class="row",
div(class="col-lg-4",
div(class="form-group shiny-input-container",
tags$label(HTML("Use Current Expression?")),
switchInput(inputId = "survival_exp_con",value = F,onLabel = "Yes",offLabel = "No")
)
),
conditionalPanel("!input.survival_exp_con",
div(class="col-lg-6",style="padding:0px",id="surv_exp_data_panel",
fileInput(inputId="survival_exp_data",label = "Expression Data")
)
)
),
conditionalPanel("!input.survival_exp_con",
div(class="row",
div(class='col-lg-12',
prettyRadioButtons(inputId = 'survival_exp_seperator',label = 'Seprator',choices = c("Tab"="\t",'Comma'=',','Space'=' ','Semicolon'=';'),status='primary',inline=T)
),
div(class="col-lg-12",
prettyRadioButtons(inputId = 'survival_exp_header',label = 'Header',choices = c("With header"=T,'Without header'=F),selected=T,status='primary',inline=T)
),
div(class="col-lg-12",
prettyRadioButtons(inputId = 'survival_exp_first_column',label = 'First Column For Row Name?',choices = c("Yes"=T,'No'=F),selected=T,status='primary',inline=T)
)
)
)
)
),
div(class="col-lg-3",
tags$fieldset(
tags$legend(HTML("Valid Patiens")),
div(class="col-lg-12",id="survival_valid_sample_panel",style="padding:0px;margin:0px",
uiOutput(outputId = "clinical_patient_count",class="col-lg-12"),
uiOutput(outputId = "exp_patient_count",class="col-lg-12"),
uiOutput(outputId = "clinical_valid_patient_count",class="col-lg-12")
)
)
),
# tags$br(),
div(class="col-lg-12",style="padding:0px",
tags$fieldset(
tags$legend("Survival Model Parameter"),
div(class="row",
div(class="col-lg-3",
pickerInput(inputId = "survival_model",label = "Survival Model",choices = c("Kaplan-Meier Analysis"="km_analysis",'Cox Model'='cox_model'))#,'Random Survival Forest'='random.forest'))
),
div(class="col-lg-3",
pickerInput(inputId='clinical_survival_time',label="Survival Time",choices = c(),options = list(title="Select Column for Survival Time"))
),
div(class="col-lg-3",
pickerInput(inputId='clinical_survival_status',label="Survival Status",choices = c(),options = list(title="Select Column for Survival Status"))
),
div(class='col-lg-3',
pickerInput(inputId = "clinical_survival_status_variable",label = "Censor Label (For \"Alive\" or \"Lost\")",choices = c())
)
),
conditionalPanel("input.survival_model!='km_analysis'",
div(class="row",
div(class="col-lg-4",
pickerInput(inputId = "survival_extern_factor_continous",label = "External Included Continus Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
),
div(class="col-lg-4",
pickerInput(inputId = "survival_extern_factor_categorical",label = "External Included Categorical Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
),
div(class="col-lg-4",
pickerInput(inputId = "survival_stratified_factor",label = "Stratified Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
)
)
),
div(class="row",
div(class="col-lg-3",
pickerInput(inputId = "clinical_gene_source",label = "Gene Set Source",choices = c("Modules"="module",'Single Gene'='single.gene','Custom'='custom'))
),
conditionalPanel("input.clinical_gene_source=='module'",
div(class="col-lg-3",
pickerInput(inputId = "clinical_module",label = "Module ID",choices = c(),multiple = T,options = list("actions-box"=T))
),
conditionalPanel("input.survival_model=='cox_model'",
div(class="col-lg-3",
div(class="form-group shiny-input-container",
tags$label("Cluster Patients with Module?"),
switchInput(inputId = "survival_module_cluster_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
)
),
conditionalPanel("input.clinical_gene_source=='single.gene'",
conditionalPanel("input.survival_model!='km_analysis'",
div(class='col-lg-2',
div(class="form-group shiny-input-container",
tags$label("Seprate Patients with Expression?"),
switchInput(inputId = "survival_single_group_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
),
conditionalPanel("input.survival_model=='km_analysis'||input.survival_single_group_sample",
div(class="col-lg-3",
sliderTextInput(inputId = "single_quantile",label = "Bifurcate Quantile",choices = seq(0,1,0.05),selected = 0.5,animate = F,grid = T)
)
),
div(class='col-lg-10',
textAreaInput(inputId = "clinical_single_gene",label = "Gene Label",value = "",placeholder = "Please Input Gene Name",rows = 10,resize = 'none')
)
),
conditionalPanel("input.clinical_gene_source=='custom'",
conditionalPanel("input.survival_model!='km_analysis'",
div(class='col-lg-3',
div(class="form-group shiny-input-container",
tags$label("Cluster Patients with Custom Gene Set?"),
switchInput(inputId = "survival_custom_cluster_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
),
div(class="col-lg-10",
textAreaInput(inputId="survival_custom_gene_input",label = "Custom Gene Set",value = "",width = "100%",rows = 10,placeholder = "Input Custom Genes",resize = 'none')
)
)
),
tags$hr()
)
),
div(class="row",
div(class="col-lg-2 pull-right",
tags$button(class="btn btn-block btn-primary pull-right",type="button",HTML("Execute"),onclick="survival(this)")
)
)
),
tabPanel(title="Clinical Data Preview",div(id="clinical_data_preview",style="margin:10px")),
tabPanel(title="Expression Data Preview",div(id="survival_exp_preview",style="margin:10px"))
)
)
),
div(id="survival_result_panel",class="row")
)
analysis_tab=tabItem(tabName = "analysis",
tabsetPanel(type="pills",
network_property_panel,
network_module_panel,
enrichment_panel,
survival_panel
)
)
william0701/CeNetOmnibus documentation built on April 11, 2021, 9:38 a.m.
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create_property_checkboxgroup=function(type,id,label,items,f)
{
selection=list()
for(i in items)
{
s=div(class="btn-group btn-goup-toggle",
tags$button(class="btn checkbtn btn-primary",type=type,
tags$span(class="check-btn-icon-yes",tags$i(class='glyphicon glyphicon-ok')),
tags$span(class="check-btn-icon-no"),
tags$input(type='checkbox',autocomplete="off",name=paste(type,"_centrality",sep=""),value=i,HTML(i),onchange=paste(f,"(this)",sep=""))
)
)
selection=c(selection,list(s))
}
ui=div(class='form-group shiny-input-container shiny-input-container-inline',
tags$label(class='control-label',HTML(label)),
tags$br(),
div(id=id,class='checkboxGroupButtons shiny-bound-input',
div(class='btn-group btn-group-container-sw',"data-toggle"="buttons","aria-label"="...",
selection
)
)
)
return(ui)
}
network_property_panel=tabPanel(title="Network Topology Properties",
h2("Part1: Network Topology Properties",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class="box-header",
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class='btn btn-box-tool',"data-widget"="collapse",
tags$i(class='fa fa-minus')
)
)
),
div(class="box-body",
create_property_checkboxgroup(type='node',id='node_centrality',label='Nodes Centrality',
items=c("Degree","Betweenness","Closeness",'Clustering Coefficient'),f='showNodeCentrality'),
create_property_checkboxgroup(type='edge',id='edge_centrality',label='Edges Centrality',items=c("Betweenness"),f='showEdgeCentrality'),
tags$br(),
div(id="network_property",class="row")
),
div(class='box-footer',
div(class='pull-right',
downloadButton(outputId='export_network_node_property', label = "Export Node Property"),
downloadButton(outputId='export_network_edge_property', label = "Export Edge Property"),
downloadButton(outputId='export_network_property_plot', label = "Export Plots")
)
)
)
)
network_module_panel=tabPanel(title="Network Modules",
h2("Part2: Network Modules",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class='box-header',
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class='btn btn-box-tool',"data-widget"="collapse",
tags$i(class='fa fa-minus')
)
)
),
div(class='box-body',
div(class="row",
div(class="col-lg-4 col-xs-6",
pickerInput(inputId = 'community_algorithm',label = 'Community Detection Algorithm',
choices = c("NG Algorithm"="cluster_edge_betweenness",
"Modularity Optimization"="cluster_fast_greedy",
"Label Propagation"="cluster_label_prop",
"Louvain Method"="cluster_louvain",
"Maximal Modularity"="cluster_optimal",
"Random Walk"="cluster_walktrap",
"InfoMap"="cluster_infomap",
"Cograph Community"="cluster_cograph",
"Markov Clustering"="cluster_mcl",
"Linkcomm"="cluster_linkcomm",
"MCODE"="cluster_mcode"
),
width = "100%"
)
),
div(class="col-lg-3 col-xs-6",style="padding:0;margin:0",
div(class="form-group shiny-input-container",
tags$label(class="control-label",HTML(" ")),
div(class="btn-group",style="display:table-row",
#tags$label(class="control-label"),tags$br(),
tags$button(id="community_para_check",class="btn btn-warning",HTML("Choose Parameter"),onclick="run_parameter_choose(this)"),
tags$button(id="community_detection",class="btn btn-primary",HTML("Perform"),onclick="run_community_detection(this)"
)
)
)
)
),
div(class="row",
div(class="col-lg-12",
conditionalPanel("input.community_algorithm=='cluster_edge_betweenness'"),
conditionalPanel("input.community_algorithm=='cluster_fast_greedy'"),
conditionalPanel("input.community_algorithm=='cluster_label_prop'"),
conditionalPanel("input.community_algorithm=='cluster_louvain'"),
conditionalPanel("input.community_algorithm=='cluster_optimal'"),
conditionalPanel("input.community_algorithm=='cluster_walktrap'",
div(class="col-lg-4",style="padding-left:0",
numericInput(inputId="walktrap_step",label = "Steps",value = 4,min=1,max=NA,step = 1,width = "100%")
)
),
conditionalPanel("input.community_algorithm=='cluster_infomap'",
div(class="col-lg-4",style="padding-left:0",
numericInput(inputId="infomap_nb_trails",label = "Module Counts",value = 10,min=2,max=NA,step = 1)
)
),
conditionalPanel("input.community_algorithm=='cluster_cograph'"),
conditionalPanel("input.community_algorithm=='cluster_mcl'",
div(class='row',
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_expansion",label = "Expansion",value = 2,min = 1,max = Inf,step = 0.1,width = "100%")
),
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_inflation",label = "Inflation",value = 2,min = 1,max = Inf,step = 0.1,width = "100%")
),
div(class='col-lg-2 col-md-6',
numericInput(inputId="mcl_max_iter",label = "Maximal Iteration",value = 100,min = 1,max = Inf,step = 1,width = "100%")
)
)
),
conditionalPanel("input.community_algorithm=='cluster_linkcomm'",
div(class='row',
div(class='col-lg-4',
pickerInput(inputId = "linkcomm_hcmethod",label = "Hierarchical Clustering Method ",
choices = c("average"="average",'ward'='ward','single'='single','complete'='complete','mcquitty'='mcquitty','median'='median','centroid'='centroid'),
selected='average',width="100%"
)
)
)
),
conditionalPanel("input.community_algorithm=='cluster_mcode'",
div(class="row",
div(class="col-lg-2",
numericInput(inputId='mcode_vwp',label = "Vertex Weight Percentage",value = 0.5,min = 0,max = 1,step = 0.1,width = '100%')
),
div(class="col-lg-2",
div(class='form-group shiny-input-container',
tags$label(HTML("Haircut")),
switchInput(inputId='mcode_haircut',value = F,onLabel = 'True',offLabel = "False")
)
)
),
div(class="row",
div(class="col-lg-2",
div(class='form-group shiny-input-container',
tags$label(HTML("Fluff")),
switchInput(inputId='mcode_fluff',value = F,onLabel = 'True',offLabel = "False")
)
)
# conditionalPanel("input.mcode_fluff",
# div(class="col-lg-2",
# numericInput(inputId='mcode_fdt',label = "Cluster Density Cutoff",value = 0.8,min = 0,max = 1,step = 0.1,width = '100%')
# )
# )
)
),
tags$br()
)
),
div(class="row",
div(class="col-lg-12",
tags$label(HTML("Module Summary"),downloadButton(outputId = "export_module_info",label = "Export")),
div(id="module_info_box")
)
),
div(class='row',
div(class="col-lg-12",
tags$label(HTML("Module Visualization")),
div(id="module_visualization",class='row')
)
)
),
div(class='box-footer',
conditionalPanel('input.community_algorithm=="cluster_edge_betweenness"',
tags$cite(class="bg-orange-active",HTML("* Newman M E J, Girvan M. Finding and evaluating community structure in networks[J]. Physical review E, 2004, 69(2): 026113."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_fast_greedy"',
tags$cite(class="bg-orange-active",HTML("* Clauset A, Newman M E J, Moore C. Finding community structure in very large networks[J]. Physical review E, 2004, 70(6): 066111."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_label_prop"',
tags$cite(class="bg-orange-active",HTML("* Raghavan U N, Albert R, Kumara S. Near linear time algorithm to detect community structures in large-scale networks[J]. Physical review E, 2007, 76(3): 036106.",style="font-weight:bold"))
),
conditionalPanel('input.community_algorithm=="cluster_louvain"',
tags$cite(class="bg-orange-active",HTML("* Blondel V D, Guillaume J L, Lambiotte R, et al. Fast unfolding of communities in large networks[J]. Journal of statistical mechanics: theory and experiment, 2008, 2008(10): P10008."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_optimal"',
tags$cite(class="bg-orange-active",HTML("* Brandes U, Delling D, Gaertler M, et al. On modularity clustering[J]. IEEE transactions on knowledge and data engineering, 2007, 20(2): 172-188."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_walktrap"',
tags$cite(class="bg-orange-active",HTML("* Pons P, Latapy M. Computing communities in large networks using random walks[C]//International symposium on computer and information sciences. Springer, Berlin, Heidelberg, 2005: 284-293."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_infomap"',
tags$cite(class="bg-orange-active",HTML("* Rosvall M, Bergstrom C T. Maps of information flow reveal community structure in complex networks[J]. arXiv preprint physics.soc-ph/0707.0609, 2007."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_cograph"',
tags$cite(class="bg-orange-active",HTML("* Jia S, Gao L, Gao Y, et al. Defining and identifying cograph communities in complex networks[J]. New Journal of Physics, 2015, 17(1): 013044."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_mcl"',
tags$cite(class="bg-orange-active",HTML("* Stijn van Dongen, Graph Clustering by Flow Simulation. PhD thesis, University of Utrecht, May 2000."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_linkcomm"',
tags$cite(class="bg-orange-active",HTML("* Ahn Y Y, Bagrow J P, Lehmann S. Link communities reveal multiscale complexity in networks[J]. nature, 2010, 466(7307): 761."),style="font-weight:bold")
),
conditionalPanel('input.community_algorithm=="cluster_mcode"',
tags$cite(class="bg-orange-active",HTML("* Bader G D, Hogue C W V. An automated method for finding molecular complexes in large protein interaction networks[J]. BMC bioinformatics, 2003, 4(1): 2."),style="font-weight:bold")
)
)
),
div(id="community_table")
)
enrichment_panel=tabPanel(title="Enrichment Analysis",
h2("Part3: Enrichment Analysis",style='font-family:Georgia'),
fluidRow(
box(width = 7,
title = "Select parameters",collapsible = T,collapsed = F,status = 'primary',solidHeader=T,
footer=tags$button(id="enrichment_finish",class="btn btn-primary btn-flat action-button shiny-bound-input",
HTML("Perform"),onclick="run_enrichment_finish(this)"),
div(class='row',
div(class='col-lg-6',
prettyRadioButtons(
inputId = "gProfileOnline_Or_custom_analysis",
label = "Enrichment Source",
choices = c("g:Profile (Online)"="gProfile", "Custom Input"="custom_input"),
inline = TRUE
)
),
conditionalPanel("input.gProfileOnline_Or_custom_analysis=='gProfile'",
div(class='col-lg-6',
pickerInput(inputId = 'Organism_enrichment',label = 'Organism:',
choices = c(),
options = list(size = 8,`live-search` = TRUE),
width = "100%"
)
),
div(class="col-lg-12",
pickerInput(inputId = 'enrichment_Data_Sources',label = 'Data Sources',
choices = c("GO Molecular Function(MF)"="GO:MF",
"GO Cellular Component(CC)"="GO:CC",
"GO Biological Process(BP)"="GO:BP",
"KEGG"="KEGG",
"Reactome"="REAC",
"WikiPathways"="WP"
),
multiple = TRUE,
options = list("actions-box"=T)
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Significance_threshold',label = 'Significance threshold',
choices = c("Benjamini-Hochberg FDR"="fdr","g:SCS threshold"="g_SCS","Bonferroni Correction"="bonferroni")
)
)
),
conditionalPanel("input.gProfileOnline_Or_custom_analysis=='custom_input'",
div(class='col-lg-10',
fileInput(inputId="enrichment_Custom_input_function_gene",label = "Custom input function gene")
),
div(class="col-lg-2",style="padding-left:0px;padding-top:5px;margin:0",
div(class="form-group shiny-input-container",
div(class="input-group-btn"),tags$br(),
tags$button(id="show_custom_input_file",class="btn btn-primary btn-flat action-button shiny-bound-input",
HTML("Preview"),onclick="run_show_custom_input_file(this)")
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Significance_threshold_custom',label = 'Significance threshold',
choices = c("Original P-value"="","Benjamini-Hochberg FDR"="fdr","Bonferroni Correction"="bonferroni")
)
)
),
div(class='col-lg-6',
numericInput(inputId = "enrichment_User_threshold", label = "User threshold", value = 0.05,min = 0,max = 1,step = 0.01)
)
),
div(class='row',
div(class='col-lg-6',
prettyRadioButtons(
inputId = "choose_which_gene_to_analysis",
label = "Gene Set Source",
choices = c("Modules Gene"="Modules_Gene", "Custom Gene"="Custom_Gene"),
inline = TRUE
)
),
conditionalPanel("input.choose_which_gene_to_analysis=='Modules_Gene'",
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Module_analysis1',label = 'Module analysis',
choices = c(),
multiple = TRUE,
options = list(size = 8,`live-search` = TRUE,"actions-box"=T),
width = "100%"
)
)
),
conditionalPanel("input.choose_which_gene_to_analysis=='Custom_Gene'",
div(class='col-lg-12',
textAreaInput(inputId="custom_input_gene",label = "Custom input gene",
value ="",placeholder = "Please input gene set, one gene per line...",
height = "100px")
)
),
div(class='col-lg-6',
pickerInput(inputId = 'enrichment_Numeric_IDs_treated_as',label = 'Gene ID Map',
choices = c(),
options = list(size = 8,`live-search` = TRUE)
)
),
div(class="col-lg-6",
prettyRadioButtons(
inputId = "enrichment_choose_show",
label = "Plot Type",
choices = c("Bar Plot"="bar_plot", "Point Plot"="point_plot"),
inline = TRUE
)
)
)
),
box(width = 5,
title = "Custom Gene Preview",collapsible = T,collapsed = F,status = 'primary',solidHeader=T,
formattableOutput('custom_preview_panel',width = '30%')
)
),
div(id="all_enrichment_show")
)
survival_panel=tabPanel(title="Survival Analysis",
h2("Part4: Survival Analysis",style='font-family:Georgia'),
div(class="box box-solid box-primary",
div(class="box-header",
h3(class="box-title"),
div(class="box-tools pull-right",
tags$button(class="btn btn-box-tool","data-widget"="collapse",
tags$i(class="fa fa-minus")
)
)
),
div(class="box-body",
tabsetPanel(type="tabs",
tabPanel(title="Parameter",
div(class="col-lg-4",style="padding:0px",
tags$fieldset(
tags$legend(HTML("Clinical Information")),
div(class='col-lg-6',style="padding:0px",
tags$button(class="btn bg-navy btn-block btn-flat",
onclick="demo_clinical()",
tags$i(class='fa fa-upload'),
HTML("Upload Demo Data")
)),
div(class="col-lg-12",style="padding:0px",
fileInput(inputId="clinical_file",label = "Clinical Data")
),
div(class='col-lg-12',style="padding:0px",
prettyRadioButtons(inputId = 'clinical_seperator',label = 'Seprator',choices = c("Tab"="\t",'Comma'=',','Space'=' ','Semicolon'=';'),status='primary',inline=T)
),
div(class="col-lg-12",style="padding:0px",
prettyRadioButtons(inputId = 'clinical_header',label = 'Header',choices = c("With header"=T,'Without header'=F),selected=T,status='primary',inline=T)
),
div(class="col-lg-12",style="padding:0px",
prettyRadioButtons(inputId = 'clinical_first_col',label = 'First Column For Row Name?',choices = c("Yes"=T,'No'=F),selected=F,status='primary',inline=T)
)
)
),
div(class="col-lg-5",
tags$fieldset(
tags$legend(HTML("Expression Data")),
div(class="row",
div(class="col-lg-4",
div(class="form-group shiny-input-container",
tags$label(HTML("Use Current Expression?")),
switchInput(inputId = "survival_exp_con",value = F,onLabel = "Yes",offLabel = "No")
)
),
conditionalPanel("!input.survival_exp_con",
div(class="col-lg-6",style="padding:0px",id="surv_exp_data_panel",
fileInput(inputId="survival_exp_data",label = "Expression Data")
)
)
),
conditionalPanel("!input.survival_exp_con",
div(class="row",
div(class='col-lg-12',
prettyRadioButtons(inputId = 'survival_exp_seperator',label = 'Seprator',choices = c("Tab"="\t",'Comma'=',','Space'=' ','Semicolon'=';'),status='primary',inline=T)
),
div(class="col-lg-12",
prettyRadioButtons(inputId = 'survival_exp_header',label = 'Header',choices = c("With header"=T,'Without header'=F),selected=T,status='primary',inline=T)
),
div(class="col-lg-12",
prettyRadioButtons(inputId = 'survival_exp_first_column',label = 'First Column For Row Name?',choices = c("Yes"=T,'No'=F),selected=T,status='primary',inline=T)
)
)
)
)
),
div(class="col-lg-3",
tags$fieldset(
tags$legend(HTML("Valid Patiens")),
div(class="col-lg-12",id="survival_valid_sample_panel",style="padding:0px;margin:0px",
uiOutput(outputId = "clinical_patient_count",class="col-lg-12"),
uiOutput(outputId = "exp_patient_count",class="col-lg-12"),
uiOutput(outputId = "clinical_valid_patient_count",class="col-lg-12")
)
)
),
# tags$br(),
div(class="col-lg-12",style="padding:0px",
tags$fieldset(
tags$legend("Survival Model Parameter"),
div(class="row",
div(class="col-lg-3",
pickerInput(inputId = "survival_model",label = "Survival Model",choices = c("Kaplan-Meier Analysis"="km_analysis",'Cox Model'='cox_model'))#,'Random Survival Forest'='random.forest'))
),
div(class="col-lg-3",
pickerInput(inputId='clinical_survival_time',label="Survival Time",choices = c(),options = list(title="Select Column for Survival Time"))
),
div(class="col-lg-3",
pickerInput(inputId='clinical_survival_status',label="Survival Status",choices = c(),options = list(title="Select Column for Survival Status"))
),
div(class='col-lg-3',
pickerInput(inputId = "clinical_survival_status_variable",label = "Censor Label (For \"Alive\" or \"Lost\")",choices = c())
)
),
conditionalPanel("input.survival_model!='km_analysis'",
div(class="row",
div(class="col-lg-4",
pickerInput(inputId = "survival_extern_factor_continous",label = "External Included Continus Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
),
div(class="col-lg-4",
pickerInput(inputId = "survival_extern_factor_categorical",label = "External Included Categorical Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
),
div(class="col-lg-4",
pickerInput(inputId = "survival_stratified_factor",label = "Stratified Factors",choices = c(),multiple = T,options = list(`live-search` = TRUE,`actions-box`=T))
)
)
),
div(class="row",
div(class="col-lg-3",
pickerInput(inputId = "clinical_gene_source",label = "Gene Set Source",choices = c("Modules"="module",'Single Gene'='single.gene','Custom'='custom'))
),
conditionalPanel("input.clinical_gene_source=='module'",
div(class="col-lg-3",
pickerInput(inputId = "clinical_module",label = "Module ID",choices = c(),multiple = T,options = list("actions-box"=T))
),
conditionalPanel("input.survival_model=='cox_model'",
div(class="col-lg-3",
div(class="form-group shiny-input-container",
tags$label("Cluster Patients with Module?"),
switchInput(inputId = "survival_module_cluster_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
)
),
conditionalPanel("input.clinical_gene_source=='single.gene'",
conditionalPanel("input.survival_model!='km_analysis'",
div(class='col-lg-2',
div(class="form-group shiny-input-container",
tags$label("Seprate Patients with Expression?"),
switchInput(inputId = "survival_single_group_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
),
conditionalPanel("input.survival_model=='km_analysis'||input.survival_single_group_sample",
div(class="col-lg-3",
sliderTextInput(inputId = "single_quantile",label = "Bifurcate Quantile",choices = seq(0,1,0.05),selected = 0.5,animate = F,grid = T)
)
),
div(class='col-lg-10',
textAreaInput(inputId = "clinical_single_gene",label = "Gene Label",value = "",placeholder = "Please Input Gene Name",rows = 10,resize = 'none')
)
),
conditionalPanel("input.clinical_gene_source=='custom'",
conditionalPanel("input.survival_model!='km_analysis'",
div(class='col-lg-3',
div(class="form-group shiny-input-container",
tags$label("Cluster Patients with Custom Gene Set?"),
switchInput(inputId = "survival_custom_cluster_sample",label = "",value = T,onLabel = "Yes",offLabel = "No")
)
)
),
div(class="col-lg-10",
textAreaInput(inputId="survival_custom_gene_input",label = "Custom Gene Set",value = "",width = "100%",rows = 10,placeholder = "Input Custom Genes",resize = 'none')
)
)
),
tags$hr()
)
),
div(class="row",
div(class="col-lg-2 pull-right",
tags$button(class="btn btn-block btn-primary pull-right",type="button",HTML("Execute"),onclick="survival(this)")
)
)
),
tabPanel(title="Clinical Data Preview",div(id="clinical_data_preview",style="margin:10px")),
tabPanel(title="Expression Data Preview",div(id="survival_exp_preview",style="margin:10px"))
)
)
),
div(id="survival_result_panel",class="row")
)
analysis_tab=tabItem(tabName = "analysis",
tabsetPanel(type="pills",
network_property_panel,
network_module_panel,
enrichment_panel,
survival_panel
)
)
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