/
ui.R
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ui.R
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ui <- fluidPage(
tags$head(tags$script(src = "message-handler.js")),
navbarPage(theme = shinytheme("yeti"), # other options: "cosmo","yeti","lumen"
title = "CELLector",
tabPanel(title = "Select Cell Lines",
fluidRow(
column(2,
a(img(src="Cancer-dependency-map-logo-MAIN-Transparent.png",
height = 83, width = 146, align = "middle"),
href='https://depmap.sanger.ac.uk/',target="_blank")
),
column(2,
a(img(src="Dep Map Analytics Logo lighter.png",
height = 76, width = 150, align = "middle"),
href='https://www.sanger.ac.uk/science/groups/cancer-dependency-map-analytics',target="_blank")
),
column(2,
a(img(src="Asset 1.png",
height = 63, width = 140, align = "middle"),
href='https://cellmodelpassports.sanger.ac.uk/',target="_blank")
),
column(2,
a(img(src="cti_ot_primary_logo_blk_hr.jpg", height = 51, width = 140, align = "middle"),
href='https://www.opentargets.org/',target="_blank")
),
column(2,
a(img(src="EMBL_EBI_Logo_black.jpg",
height = 41, width = 139, align = "middle"),
href='https://www.ebi.ac.uk/',target="_blank")
),
column(2,
a(img(src="Wellcome_Sanger_Institute_Logo_Landscape_Digital_RGB_Monotone_Black.png",
height = 52, width = 152, align = "middle"),
href='http://www.sanger.ac.uk/',target="_blank")
)
),
br(),
fluidRow(
column(5,
a(img(src="Cellector-logo-double-size.png", align = "middle"))
),
column(7,
titlePanel(div(HTML("Genomics Guided Selection of Cancer <em>in vitro</em> Models"))),
hr(),
h3('v1.0.3'),
p(h5(a("Tutorial", href="https://rpubs.com/francescojm/CELLector_App" ,
target="_blank"))),
p(h5(a("Code", href="https://github.com/francescojm/CELLector_App" ,
target="_blank"))),
p(h5(a("CELLector R Package", href="https://github.com/francescojm/CELLector" ,
target="_blank"))),
p(h5(a("CELLector R Package interactive vignette", href="https://rpubs.com/francescojm/CELLector" ,
target="_blank")))
)
),
verbatimTextOutput("str"),
fluidRow(
# - - - - - - - - - - - - - - - - - - - - -
column(3,
wellPanel(
img(src="cellcultures.jpg", height = 100, width = 240, align = "middle"),
br(), br(),
wellPanel(
checkboxInput('UDgenomic', 'User Defined Binary genomic Event Matrices (BEMs)', FALSE),
conditionalPanel(condition = 'input.UDgenomic',
fileInput("ud_tumourBEMs", "Select Primary Tumour BEMs file:",
multiple = FALSE,
accept = c(".RData")),
fileInput("ud_cellLineBEMs", "Select Cell Line BEMs file:",
multiple = TRUE,
accept = c(".RData")),
actionButton('ValidateUpdateBEMs','Validate and update BEMs')
),
conditionalPanel(condition = '!input.UDgenomic',
selectInput("selectCancerType", label = h5("Cancer Type:"),
choices = sort(as.character(TCGALabels)), selected = 'COREAD'),
p(h6("Underlying data available at the", a("GDSC1000 data portal.", href="http://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources/Home.html" ,
target="_blank")))
)
),
actionButton("action", label = tags$strong(em("Build Search Space"))),
br(), br(),
downloadButton("DownSearchSpace", label = "Download Search Space"),
br(), br()
),
fluidRow(column(12,
wellPanel(
h5("Representative Cell Line Selection"),
numericInput("N.CellLines", h5(strong(em("N. of Cell Lines to Select:"))), 10, min = 1, max = 100),
downloadButton("CELLect", label = "CELLect Cell Lines"),
br(),
downloadButton("score", "Score cell lines"),
downloadButton("subTypeMap", "Cell lines SubTypes Map"),
sliderInput("scoreAlpha",min = 0,max=1,
strong(paste("\nSignature Length weight (= 1 - n. Patients score weight)")),
value = 0.75,
step = 0.05,round = TRUE),
p(h6("Please cite:",
a("Najgebauer et al. 2018 - CELLector: Genomics Guided Selection of Cancer in vitro Models", href = "https://www.biorxiv.org/content/early/2018/03/03/275032" , target="_blank")))
)) )
),
# - - - - - - - - - - - - - - - - - - - - -
column(9,
wellPanel(
h5("Primary Tumours: Subtyping Criteria"),
fluidRow(
column(5,
conditionalPanel("!input.UDgenomic",
radioButtons('whatToInclude', strong('Cancer Functional Events (CFEs) to consider:'),
choices = c('Mutations in high confidence cancer genes',
'Recurrently CN altered chromosomal segments',
'Both'),
selected = 'Both',
inline = FALSE),
checkboxGroupInput("useMeth",label=NULL,
choices = list("Include Methylation data" = 1),
selected = NULL)
)
),
column(7,
fluidRow(
column(6,sliderInput("minSetSize",
strong("Alteration set size:"), 1, 5, value = 1,step = 1,round = TRUE)),
column(6,
sliderInput("minGlobalSupport",
strong("Global support (%):"), 1, 50, value = 5,step = 1,round = TRUE)
)
)
)
)
)
),
# - - - - - - - - - - - - - - - - - - - - -
column(3,conditionalPanel("!input.UDgenomic",
wellPanel(
p(h5("Supervised Search Space Construction")),
br(),
# - - - - - - - - - - - - - - - - - - - - -
fluidRow(
column(6,
selectizeInput(
'subSet',
label = "1. Define subcohort based on the status of an individual CFE:",
choices = c('', features),
selected = '',
options = list(create = TRUE, maxItems = 1)
),
checkboxInput("checkboxNegation", label = "wild-type", value = FALSE),
selectizeInput(
'pathFocus',
label = "2. Focus on CFEs in cancer pathways (max 3):",
choices = c('',pathways),
selected="",
options = list(create = TRUE, maxItems = 3)
),
radioButtons('whatToInclude2', '3. Consider only cell lines that are:',
choices = c('Microsatellite stable',
'Microsatellite instable',
'All'),
selected = 'All',
inline = FALSE)
)
)
)
)
),
# - - - - - - - - - - - - - - - - - - - - -
column(6,conditionalPanel("!input.UDgenomic",
checkboxInput('showCNAdecode', 'Show CNA id decoding table', TRUE),
conditionalPanel(condition = 'input.showCNAdecode',
wellPanel(
p(h5("Id decoding for recurrently CN altered chromosomal segments (values in Id column can be used in box 1)")),
dataTableOutput('cnaDecodeTable'),
p(h6("Full decoding table available at the", a("GDSC1000 data portal",
href = "http://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources//Data/suppData/TableS2D.xlsx" , target="_blank")))
)
),
checkboxInput('showHMSdecode', 'Show HyperMeth. id decoding table', FALSE),
conditionalPanel(condition = 'input.showHMSdecode',
wellPanel(
p(h5("Id decoding for informative CpG island hyper-methylations (values in Id column can be used in box 1)")),
dataTableOutput('hmsDecodeTable'),
p(h6("Full decoding table available at the", a("GDSC1000 data portal",
href = "http://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources//Data/suppData/TableS2D.xlsx" , target="_blank")))
)
)
)
)
),
# # - - - - - - - - - - - - - - - - - - - - -
actionButton('changeColors','Use Different Color Scheme'),
fluidRow(
column(9,
wellPanel(
collapsibleTreeOutput("plot"))
),
column(3,
sunburstOutput("sunburst"))
),
fluidRow(
column(6,
tableOutput('NodeDetails'),
tableOutput('CellLineDetails')),
column(3,plotOutput('GlobalPieChart')),
column(3,plotOutput('ComplementPieChart'))
)
),
tabPanel(title = "BEM builder",
fluidRow(
column(4,
a(img(src="Cellector-logo-double-size.png", height = 131, width = 216, align = "middle"))
),
column(4,
a(img(src="cti_ot_primary_logo_blk_hr.jpg", height = 57, width = 156, align = "middle"),
href='https://www.opentargets.org/',target="_blank")
),
column(4,
a(img(src="Wellcome_Sanger_Institute_Logo_Landscape_Digital_RGB_Monotone_Black.png",
height = 58, width = 169, align = "middle"),
href='http://www.sanger.ac.uk/',target="_blank")
),
column(4,
a(img(src="EMBL_EBI_Logo_black.jpg",
height = 46, width = 155, align = "middle"),
href='https://www.ebi.ac.uk/',target="_blank")
)
),
br(),
titlePanel(div(HTML("Genomic Binary Event Matrix (BEM) builder"))),
hr(),
h3('v1.0.1'),
p(h5(a("Tutorial", href="https://www.dropbox.com/s/djaaj2b33hqv4w1/Supplemental_Information.pdf?dl=1" ,
target="_blank"))),
p(h5(a("Code", href="https://github.com/francescojm/CELLector_App" ,
target="_blank"))),
p(h5(a("CELLector R Package", href="https://github.com/francescojm/CELLector" ,
target="_blank"))),
p(h5(a("CELLector R Package interactive vignette", href="https://rpubs.com/francescojm/CELLector" ,
target="_blank"))),
column(6,
wellPanel(
h4(strong("Primary tumours")),
radioButtons('USE_whatTumData',"Variant catalogue to consider:",
choices = c('Use curated TCGA data from Iorio et al. 2016',
'Upload Variants'),
selected = 'Use curated TCGA data from Iorio et al. 2016'),
conditionalPanel(condition = "input.USE_whatTumData == 'Use curated TCGA data from Iorio et al. 2016'",
wellPanel(
selectInput("TCGA_selectCancerType", label = h5("Cancer Type:"),
choices = sort(unique(CELLector.PrimTumVarCatalog$Cancer.Type)),
selected = sort(unique(CELLector.PrimTumVarCatalog$Cancer.Type))[1]),
radioButtons("TCGA_genes", 'Genes to consider:',
choices = c('All','Iorio et al. 2016 drivers','CMPs drivers','User defined list'),
selected = 'Iorio et al. 2016 drivers',
inline = TRUE),
conditionalPanel(condition = "input.TCGA_genes == 'User defined list'",
fileInput("TCGA_ud_geneList",
"Upload a plain .txt file with Gene identifiers (one per line):",
multiple = FALSE,
accept = c(".txt"))),
radioButtons("TCGA_variants", 'Variants to consider:',
choices = c('All','Iorio et al. 2016 variants (COSMIC filtered)','User defined list'),
selected = 'Iorio et al. 2016 variants (COSMIC filtered)',
inline = TRUE),
conditionalPanel(condition = "input.TCGA_variants == 'User defined list'",
fileInput("TCGA_ud_variants",
"Upload a plain .txt file with tab separated [Gene identifier - variant] (one pair per line):",
multiple = FALSE,
accept = c(".txt")))
)
),
conditionalPanel(condition = "input.USE_whatTumData !='Use curated TCGA data from Iorio et al. 2016'",
wellPanel(
fileInput("TCGA_ud_variant_catalogue",
"Upload the variant catalogue as a plain tab separated .txt file:",
multiple = FALSE,
accept = c(".txt"))
)
),
fluidRow(
column(4,actionButton('TGCA_BEM_generation','Make new BEM')),
column(4,radioButtons('TGCA_BEM_AS_WHAT', strong('BEM file format:'),
choices = c('R object','.tsv'),
selected = 'R object',
inline = TRUE)),
column(4,downloadButton('SAVE_TCGA_BEM','Save BEM'))
),
verbatimTextOutput("str_UD_TCGA_BEM_STATUS")
)
),
column(6,
wellPanel(
h4(strong("in-vitro models")),
radioButtons('USE_cellModelPassports',"Variant catalogue to consider:",
choices = c('Use Variants Catalogue from Cell Model Passports (CMPs)',
'Upload Variants'),
selected = 'Use Variants Catalogue from Cell Model Passports (CMPs)'),
conditionalPanel(condition = "input.USE_cellModelPassports == 'Use Variants Catalogue from Cell Model Passports (CMPs)'",
wellPanel(
fluidRow(
column(3,
checkboxInput('CMP_exclude_organoids', 'Exclude organoids', FALSE),
checkboxInput('CMP_human_samples_only', 'Human derived only', TRUE),
wellPanel(
checkboxInput('CMP_age_at_sampling', 'Filter based on age at sampling', TRUE),
conditionalPanel(condition = "input.CMP_age_at_sampling",
uiOutput("CMP_age_at_sampling_slide_uiOutput")
))
),
column(3,radioButtons('CMP_gender',label = 'Gender:',choices = c('Male','Female','All (including Unknown)'),
selected = 'All (including Unknown)'),
wellPanel(
checkboxInput('CMP_based_on_etnicity',label='Filter based on etnicity'),
conditionalPanel(condition = "input.CMP_based_on_etnicity",
uiOutput("CMP_etnicity_uiOutput")
))
),
column(3,radioButtons('CMP_msi_status',label = 'MSI status:',
choices = c('MSS','MSI','All (including NA)'),
selected = 'All (including NA)')),
column(3,
wellPanel(
checkboxInput('CMP_based_on_mut_burden',label='Filter based on mutation burden',value = TRUE),
conditionalPanel(condition = "input.CMP_based_on_mut_burden",
uiOutput("CMP_mutBurdend_slide_uiOutput")
)),
wellPanel(
checkboxInput('CMP_based_on_ploidy',label='Filter based on ploidy',value = TRUE),
conditionalPanel(condition = "input.CMP_based_on_ploidy",
uiOutput("CMP_ploidy_slide_uiOutput")
))
)
),
uiOutput("CMP_N_cell_lines"),
selectInput("CMP_selectTissue", label = h5("Tissue:"),
choices = sort(unique(CMPs_model_annotations$tissue)),
selected = sort(unique(CMPs_model_annotations$tissue))[1]),
uiOutput("CMP_selectCancerType_uiOutput"),
uiOutput("CMP_selectCancerType_details_uiOutput"),
uiOutput("CMP_selectSample_site_uiOutput"),
radioButtons("CMP_genes", 'Genes to consider:',
choices = c('All','Iorio et al. 2016 drivers','CMPs drivers','User defined list'),
selected = 'Iorio et al. 2016 drivers',
inline = TRUE),
conditionalPanel(condition = "input.CMP_genes == 'User defined list'",
fileInput("CMP_ud_geneList",
"Upload a plain .txt file with Gene identifiers (one per line):",
multiple = FALSE,
accept = c(".txt"))),
radioButtons("CMP_variants", 'Variants to consider:',
choices = c('All','Iorio et al. 2016 variants (COSMIC filtered)','User defined list'),
selected = 'Iorio et al. 2016 variants (COSMIC filtered)',
inline = TRUE),
conditionalPanel(condition = "input.CMP_variants == 'User defined list'",
fileInput("CMP_ud_variants",
"Upload a plain .txt file with tab separated [Gene identifier - variant] (one pair per line):",
multiple = FALSE,
accept = c(".txt")))
)
),
conditionalPanel(condition = "input.USE_cellModelPassports != 'Use Variants Catalogue from Cell Model Passports (CMPs)'",
wellPanel(
fileInput("CMP_ud_variant_catalogue",
"Upload the variant catalogue as a plain tab separated .txt file:",
multiple = FALSE,
accept = c(".txt"))
)
),
fluidRow(
column(4,actionButton('CL_BEM_generation','Make new BEM')),
column(4,radioButtons('CL_BEM_AS_WHAT', strong('BEM file format:'),
choices = c('R object','.tsv'),
selected = 'R object',
inline = TRUE)),
column(4,downloadButton('SAVE_CL_BEM','Save BEM'))
),
verbatimTextOutput("str_UD_CL_BEM_STATUS")
)
)
)
)
)