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inst/ui.R
In ChromSCape: Analysis of single-cell epigenomics datasets with a Shiny App
library(shiny)
library(shinyjs)
library(dplyr)
shinyUI(shinydashboard::dashboardPage(skin='green',
shinydashboard::dashboardHeader(title = "ChromSCape"),
shinydashboard::dashboardSidebar(
shinydashboard::sidebarUserPanel("Institut Curie - Vallot Lab",
subtitle = a(href = "#", icon("circle", class = "text-success"), "Online"),
image = "curie.jpg"
),
shinydashboard::sidebarMenu(id="tabs", style = "position: fixed; overflow: visible;",
shinydashboard::menuItem("Select & Import", tabName = "select_import", icon=icon("upload")),
shinydashboard::menuItem("Filter & Normalize", tabName = "filter_normalize", icon=icon("fas fa-filter")),
shinydashboard::menuItem("Visualize Cells", tabName = "vizualize_dim_red", icon=icon("fas fa-image")),
shinydashboard::menuItem("Cluster Cells", tabName = "cons_clustering", icon=icon("th")),
shinydashboard::menuItem("Peak Calling", tabName = "peak_calling", icon=icon("chart-area")), #mountain
shinydashboard::menuItem("Differential Analysis", tabName = "diff_analysis", icon=icon("chart-bar")),
shinydashboard::menuItem("Pathway Enrichment Analysis", tabName = "enrich_analysis", icon=icon("code-branch")),
shinydashboard::menuItem("Close App & Save Analysis", tabName = "close_and_save", icon=icon("close"))
)
),
shinydashboard::dashboardBody(
shinyjs::useShinyjs(),
tags$head(includeCSS('www/style.css')),
tags$head(includeCSS('www/introjs.min.css')),
tags$head(includeCSS('www/app.css')),
tags$style(type="text/css",
".shiny-output-error { visibility: hidden; }",
".shiny-output-error:before { visibility: hidden; }"
),
tags$head(tags$style(HTML(
'.myClass {
font-size: 20px;
line-height: 50px;
text-align: left;
font-family: "Helvetica Neue",Helvetica,Arial,sans-serif;
padding: 0 15px;
overflow: hidden;
color: white;
}
'))),
tags$script(HTML('
$(document).ready(function() {
$("header").find("nav").append(\'<div id="pageHeader" class="myClass"></div>\');
})
')),
shinydashboard::tabItems(
###############################################################
# 1. Select Analysis & Import dataset
###############################################################
shinydashboard::tabItem(tabName = "select_import",
fluidPage(
# Add ressources for UX
shiny::includeScript(file.path(system.file(package="ChromSCape"),"js.cookie.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"intro.min.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"app.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"www","shiny_js_functions.js")),
#Load shinyJS added functions
shinyjs::extendShinyjs(script = file.path(system.file(package="ChromSCape"),"www","shiny_js_functions.js"),
functions = c("init_directory","save_cookie","disableTab","enableTab")),
#Center Panel
column(width=6,align="left",
shinydashboard::box(title="Select output directory", width = NULL, status="success",
solidHeader=TRUE,
column(12, align="left",
shinyFiles::shinyDirButton("data_folder", "Browse", "Upload") %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "output_directory"),
verbatimTextOutput("directory", placeholder = TRUE)),
column(12, align="left", textOutput("data_folder_info"))),
shinydashboard::box(title="Import raw data & Create new analysis", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
column(12, align="left",textInput("new_analysis_name", "Enter a name for the new analysis :", value = "Analysis_1"),
selectInput("annotation","Select reference genome:", choices=c("hg38", "mm10")),
textOutput("data_matrices_info") %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "datamatrix_input")),
column(6,
radioButtons("data_choice_box", label = "Input data type",
choices = list("Count matrix(ces)"="count_mat",
"Index, Peak & Barcode files" = "Index_Peak_Barcode",
"Single-cell BAM files" = "BAM",
"Single-cell BED files" = "BED"
))),
column(6,
uiOutput("input_data_ui")),
column(12,
uiOutput("advanced_data_input")),
column(12,actionButton("create_analysis", "Create analysis")))),
shinydashboard::box(title="Load previous analysis", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
uiOutput("selected_analysis")
)
)
),
column(width=6, align="right",
actionButton("startHelp","Help", icon = icon("question-circle"))),
)
),
###############################################################
# 2. Filter and Normalize dataset
###############################################################
shinydashboard::tabItem(tabName = "filter_normalize",
fluidPage(
#Right Panel
column(width=6,
shinydashboard::box(title="Filter & Normalize panel", width = NULL, status="success", solidHeader=TRUE,
column(8, align="left",
sliderInput("coverage_bins", "modify bin size of histogram :",
min=5, max=100, value=50, step=5)),
column(12, align="left",
plotly::plotlyOutput("cell_coverage", height=250) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75),
br(), hr(),
uiOutput("table_QC_filt_box"),
br(), hr(),
sliderInput("min_coverage_cell", shiny::HTML("<p><span style='color: green'>Select minimum number of reads per cell :</span></p>"),
min=100, max=5000, value=1600, step=100) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "filtering_parameters"),
sliderInput("quant_removal", shiny::HTML("<p><span style='color: red'>Select the upper percentile of cells to remove (potential doublets):</span></p>"),
min=80, max=100, value=95, step=1),
sliderInput("min_cells_window", "Select minimum percentage of cells to support a window :", min=0, max=20, value=1, step=0.25),
checkboxInput("run_tsne", "Run T-SNE", value= FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "run_tsne"),
checkboxInput("do_subsample", "Perform subsampling", value=FALSE)%>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "subsampling"),
uiOutput("do_subsample"),
checkboxInput("exclude_regions", "Exclude specific genomic regions", value=FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "exclude_region"),
uiOutput("exclude_file"),
checkboxInput("do_batch_corr", "Perform batch correction", value=FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "batch_correction"),
uiOutput("num_batches")),
column(5, align="left",
uiOutput("batch_names")),
column(7, align="left",
htmlOutput("batch_sel")),
column(12, align="left",
hr(),
actionButton("filter_normalize_reduce", "Filter, Normalize & Reduce")))),
column(width = 6,
shinydashboard::box(title="Select filtered & normalized dataset", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
htmlOutput("selected_reduced_dataset"),
textOutput("red_data_selection_info"),
textOutput("red_data_selection_format"))))
)
),
###############################################################
# 2. Vizualising cells in reduced dimension
###############################################################
shinydashboard::tabItem(
tabName = "vizualize_dim_red",
fluidPage(
column(width=6,
shinydashboard::box(title="PCA", width = NULL, status="success", solidHeader=TRUE,
column(6, align="left", uiOutput("feature_color")),
column(12, align="left",plotOutput("pca_plot") %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "pca_plot")
),
column(3, align="left", uiOutput("pc_select_x")),
column(3, align="left", uiOutput("pc_select_y"))),
uiOutput("color_box")),
column(width=6,
shinydashboard::box(title="UMAP", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left", plotOutput("UMAP_plot") %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "umap_plot")
)),
uiOutput("tsne_box")
)
)
),
###############################################################
# 4. Consensus clustering on correlated cells
###############################################################
shinydashboard::tabItem(tabName = "cons_clustering",
fluidPage(
column(width=6,
shinydashboard::box(title=tagList(shiny::icon("cube"),"Hierarchical Clustering"),
width=NULL, status="success", solidHeader=TRUE,
column(12, align ="center", plotOutput("hc_heatmap_plot", height=500, width=500) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "correlation_clustering"))
),
shinydashboard::box(title = tagList(shiny::icon("cubes"),"Consensus Hierarchical Clustering"),
width=NULL, status="success", solidHeader=TRUE,
collapsible = TRUE, collapsed = TRUE,
column(12, align = "left", br()),
column(12, offset = 0,
div(style="display: inline-block;vertical-align:top; width: 200px;", sliderInput("maxK", "Max cluster :", min=2, max=20, value=10, step=1)),
div(style="display: inline-block;vertical-align:top; width: 25px;",HTML("<br>")),
div(style="display: inline-block;vertical-align:top; width: 200px;", sliderInput("consclust_iter", "Number of iterations:", min=10, max=1000, value=100, step=10)),
div(style="display: inline-block;vertical-align:top; width: 25px;",HTML("<br>")),
div(style="display: inline-block;vertical-align:top; width: 200px;", selectInput("clusterAlg", "Cluster Algorithm:", choices = c("Hierarchical","Partitioning Medoids","K-means"),selected = "hc")),
br()),
column(3, align="left", actionButton("do_cons_clust", "Launch Consensus Clustering"),
br()),
column(12, align = "left",
hr()),
column(12, align ="center", uiOutput("cons_corr_clust_pca_UI")),
column(12, align="left", uiOutput("cluster_consensus_plot")),
column(12,hr()),
column(12, align="left", textOutput("cluster_consensus_info")),
column(12, align="left", uiOutput("cons_clust_pdf"))
),
shinydashboard::box(title=tagList(shiny::icon("fas fa-filter"),"Filter lowly correlated cells"),
width=NULL, status="success", solidHeader=TRUE,
collapsible = TRUE, collapsed = TRUE,
column(12, align="center",
plotOutput("cell_cor_hist_plot", height=300, width=500) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "filter_correlation_distrib")),
column(12, align = "left",
hr(),
sliderInput("corr_threshold", "Correlation threshold quantile:", min=75, max=99, value=99, step=1),
sliderInput("percent_correlation", "Minimum percentage of cells to correlate with (%)", min=0, max=15, value=1, step=0.25)),
column(3, align="left", br(),
actionButton("filter_corr_cells", "Filter & save")),
column(12, uiOutput("table_cor_filtered")
)
)
),
column(width=6,
shinydashboard::box(title="Select Cluster Number", width=NULL, status="success", solidHeader=TRUE,
align="left",
column(width=4,uiOutput("nclust_UI")),
column(width=3, br(),br(), checkboxInput("cluster_type",label = shiny::HTML("<b>Use consensus</b>"),value = FALSE)),
column(width=3,br(),br(),actionButton(inputId = "choose_cluster", label = "Choose Cluster"))
),
uiOutput("contingency_table_cluster"),
uiOutput("UMAP_box"),
uiOutput("tsne_box_cf"),
uiOutput("color_box_cf"),
shinydashboard::box(title="Correlation heatmap with cluster annotation", width=NULL,
status="success", solidHeader=TRUE, align="left",
column(width=4,
actionButton(inputId = "do_annotated_heatmap_plot", label = "Plot Clustered Heatmap"), br()),
column(width=12, uiOutput("annotated_heatmap_UI"))
)
)
)
),
###############################################################
# 5. Peak calling [optional]
###############################################################
shinydashboard::tabItem(tabName = "peak_calling",
fluidPage(
column(width=6,
shinydashboard::box(title="Peak calling", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", textOutput("peak_calling_info"), hr()),
tags$style(HTML(".large_icon { font-size: 70px; }")),
column(5, align="left",
htmlOutput("peak_calling_system"), hr()),
column(5,offset = 1,align="center", htmlOutput("peak_calling_icon")),
column(12, align="left",
sliderInput("peak_distance_to_merge", "Select distance of peaks to merge:", min=0, max=50000, value=5000, step=100),
shinyFiles::shinyDirButton("bam_folder", "Choose a folder containing the BAM files" ,
title = "Please select a folder:",
buttonType = "default", class = NULL), br(),
textOutput("bam_dir"), br(),
uiOutput("bam_upload")),
column(4, align="left", textOutput("pc_k_selection"),
selectInput("pc_stat","Select statistic for cutoff:", choices=c("p.value", "q.value"), selected="p.value")),
column(8, align="left", br(), br(), br(), br(),
sliderInput("pc_stat_value", "Select significance threshold:", min=0, max=0.25, value=0.05, step=0.01)),
column(12, align="left", hr(), actionButton("do_pc", "Start"))))
# ,column(width=6, uiOutput("pc_plot_box"))
)
),
###############################################################
# 6. Differential analysis
###############################################################
shinydashboard::tabItem(tabName = "diff_analysis",
fluidPage(
column(width=6,
shinydashboard::box(title="Differential Analysis parameters", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", textOutput("diff_analysis_info"), br()),
column(8, align="left", uiOutput("selected_k"), br()),
column(5, align="left", selectInput("da_method", "Select type of DA method:",
choices=list("Wilcoxon" = "wilcox",
"edgeR GLM" = "neg.binomial"))),
column(5, align="left", selectInput("de_type", "Select type of cluster comparison:", choices=c("one_vs_rest","pairwise"))),
column(12, align="left", sliderInput("qval.th", "Adjusted p-value to select significant features:", min=0.01, max=0.4, value=0.01, step=0.01),
sliderInput("cdiff.th", "Minimum log-fold change to select significant locations:", min=0, max=3, value=1, step=0.01)),
# plotOutput("distrib_norm_hist") %>% shinyhelper::helper(type = 'markdown',
# icon ="info-circle",
# content = "distrib_norm_hist"
# )),
# uiOutput("only_contrib_cell_ui")),
# column(1, align="left", br()),
# column(11, align="left", uiOutput("contrib_thresh")),
# column(1, align="left", br()),
# column(8, align="left", uiOutput("contrib_hist")),
# column(3, align="left", br(), uiOutput("contrib_info")),
column(12, align="left", hr(), actionButton("do_wilcox", "Start analysis"))),
uiOutput("da_summary_box")),
column(width=6,
uiOutput("da_visu_box")))
),
###############################################################
# 7. Enrichment analysis
###############################################################
shinydashboard::tabItem(tabName = "enrich_analysis",
fluidPage(
column(width=6,
shinydashboard::box(title="Enrichment analysis", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", htmlOutput("enr_info"), br(),
uiOutput("use_peaks"),
actionButton("do_enrich", "Start enrichment analysis"))),
shinydashboard::box(title="Enriched gene sets in differential regions across clusters", width=NULL, status="success", solidHeader=TRUE,
column(4, align="left", uiOutput("enr_clust_sel"), br()),
column(8, align="left", uiOutput("enr_class_sel"), br()),
column(12, align="left",
mainPanel(tabsetPanel(id='enr_tables',
tabPanel("In differential features", div(style = 'overflow-x: scroll', DT::dataTableOutput('all_enrich_table'))),
tabPanel("In enriched features", div(style = 'overflow-x: scroll', DT::dataTableOutput('over_enrich_table'))),
tabPanel("In depleted features", div(style = 'overflow-x: scroll', DT::dataTableOutput('under_enrich_table')))), width=12),
br(), br(), br(), br(), br(),
downloadButton("download_enr_data", "Download tables")))),
column(width=6,
shinydashboard::box(title="Enrichment near TSS", width=NULL, status="success", solidHeader=TRUE,
column(4, align="left", uiOutput("gene_sel")),
column(8, align="left", uiOutput("region_sel")),
column(12, align="left", uiOutput("gene_umap_UI")))))
),
###############################################################
# 8. Close app
###############################################################
shinydashboard::tabItem(tabName="close_and_save",
fluidPage(shinyjs::useShinyjs(),
# extendShinyjs(text = jscode, functions = c("closeWindow")),
column(width=6,
shinydashboard::box(title='Close App & Save Analysis', solidHeader=TRUE, status='danger', width=NULL,
column(12, actionButton("close_and_save", "Close App & Save Analysis")))
),
column(width=6,
shinydashboard::box(title="Delete analysis", width = NULL, status="success", solidHeader=TRUE,
column(9, align="left", uiOutput("selected_delete_analysis")),
column(3, align="left", br(), actionButton("delete_analysis", "Delete")),
column(12, align="left", textOutput("analysis_deletion_info"))))
)
)
)))
)
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library(shiny)
library(shinyjs)
library(dplyr)
shinyUI(shinydashboard::dashboardPage(skin='green',
shinydashboard::dashboardHeader(title = "ChromSCape"),
shinydashboard::dashboardSidebar(
shinydashboard::sidebarUserPanel("Institut Curie - Vallot Lab",
subtitle = a(href = "#", icon("circle", class = "text-success"), "Online"),
image = "curie.jpg"
),
shinydashboard::sidebarMenu(id="tabs", style = "position: fixed; overflow: visible;",
shinydashboard::menuItem("Select & Import", tabName = "select_import", icon=icon("upload")),
shinydashboard::menuItem("Filter & Normalize", tabName = "filter_normalize", icon=icon("fas fa-filter")),
shinydashboard::menuItem("Visualize Cells", tabName = "vizualize_dim_red", icon=icon("fas fa-image")),
shinydashboard::menuItem("Cluster Cells", tabName = "cons_clustering", icon=icon("th")),
shinydashboard::menuItem("Peak Calling", tabName = "peak_calling", icon=icon("chart-area")), #mountain
shinydashboard::menuItem("Differential Analysis", tabName = "diff_analysis", icon=icon("chart-bar")),
shinydashboard::menuItem("Pathway Enrichment Analysis", tabName = "enrich_analysis", icon=icon("code-branch")),
shinydashboard::menuItem("Close App & Save Analysis", tabName = "close_and_save", icon=icon("close"))
)
),
shinydashboard::dashboardBody(
shinyjs::useShinyjs(),
tags$head(includeCSS('www/style.css')),
tags$head(includeCSS('www/introjs.min.css')),
tags$head(includeCSS('www/app.css')),
tags$style(type="text/css",
".shiny-output-error { visibility: hidden; }",
".shiny-output-error:before { visibility: hidden; }"
),
tags$head(tags$style(HTML(
'.myClass {
font-size: 20px;
line-height: 50px;
text-align: left;
font-family: "Helvetica Neue",Helvetica,Arial,sans-serif;
padding: 0 15px;
overflow: hidden;
color: white;
}
'))),
tags$script(HTML('
$(document).ready(function() {
$("header").find("nav").append(\'<div id="pageHeader" class="myClass"></div>\');
})
')),
shinydashboard::tabItems(
###############################################################
# 1. Select Analysis & Import dataset
###############################################################
shinydashboard::tabItem(tabName = "select_import",
fluidPage(
# Add ressources for UX
shiny::includeScript(file.path(system.file(package="ChromSCape"),"js.cookie.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"intro.min.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"app.js")),
shiny::includeScript(file.path(system.file(package="ChromSCape"),"www","shiny_js_functions.js")),
#Load shinyJS added functions
shinyjs::extendShinyjs(script = file.path(system.file(package="ChromSCape"),"www","shiny_js_functions.js"),
functions = c("init_directory","save_cookie","disableTab","enableTab")),
#Center Panel
column(width=6,align="left",
shinydashboard::box(title="Select output directory", width = NULL, status="success",
solidHeader=TRUE,
column(12, align="left",
shinyFiles::shinyDirButton("data_folder", "Browse", "Upload") %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "output_directory"),
verbatimTextOutput("directory", placeholder = TRUE)),
column(12, align="left", textOutput("data_folder_info"))),
shinydashboard::box(title="Import raw data & Create new analysis", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
column(12, align="left",textInput("new_analysis_name", "Enter a name for the new analysis :", value = "Analysis_1"),
selectInput("annotation","Select reference genome:", choices=c("hg38", "mm10")),
textOutput("data_matrices_info") %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "datamatrix_input")),
column(6,
radioButtons("data_choice_box", label = "Input data type",
choices = list("Count matrix(ces)"="count_mat",
"Index, Peak & Barcode files" = "Index_Peak_Barcode",
"Single-cell BAM files" = "BAM",
"Single-cell BED files" = "BED"
))),
column(6,
uiOutput("input_data_ui")),
column(12,
uiOutput("advanced_data_input")),
column(12,actionButton("create_analysis", "Create analysis")))),
shinydashboard::box(title="Load previous analysis", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
uiOutput("selected_analysis")
)
)
),
column(width=6, align="right",
actionButton("startHelp","Help", icon = icon("question-circle"))),
)
),
###############################################################
# 2. Filter and Normalize dataset
###############################################################
shinydashboard::tabItem(tabName = "filter_normalize",
fluidPage(
#Right Panel
column(width=6,
shinydashboard::box(title="Filter & Normalize panel", width = NULL, status="success", solidHeader=TRUE,
column(8, align="left",
sliderInput("coverage_bins", "modify bin size of histogram :",
min=5, max=100, value=50, step=5)),
column(12, align="left",
plotly::plotlyOutput("cell_coverage", height=250) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75),
br(), hr(),
uiOutput("table_QC_filt_box"),
br(), hr(),
sliderInput("min_coverage_cell", shiny::HTML("<p><span style='color: green'>Select minimum number of reads per cell :</span></p>"),
min=100, max=5000, value=1600, step=100) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "filtering_parameters"),
sliderInput("quant_removal", shiny::HTML("<p><span style='color: red'>Select the upper percentile of cells to remove (potential doublets):</span></p>"),
min=80, max=100, value=95, step=1),
sliderInput("min_cells_window", "Select minimum percentage of cells to support a window :", min=0, max=20, value=1, step=0.25),
checkboxInput("run_tsne", "Run T-SNE", value= FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "run_tsne"),
checkboxInput("do_subsample", "Perform subsampling", value=FALSE)%>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "subsampling"),
uiOutput("do_subsample"),
checkboxInput("exclude_regions", "Exclude specific genomic regions", value=FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "exclude_region"),
uiOutput("exclude_file"),
checkboxInput("do_batch_corr", "Perform batch correction", value=FALSE) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "batch_correction"),
uiOutput("num_batches")),
column(5, align="left",
uiOutput("batch_names")),
column(7, align="left",
htmlOutput("batch_sel")),
column(12, align="left",
hr(),
actionButton("filter_normalize_reduce", "Filter, Normalize & Reduce")))),
column(width = 6,
shinydashboard::box(title="Select filtered & normalized dataset", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left",
htmlOutput("selected_reduced_dataset"),
textOutput("red_data_selection_info"),
textOutput("red_data_selection_format"))))
)
),
###############################################################
# 2. Vizualising cells in reduced dimension
###############################################################
shinydashboard::tabItem(
tabName = "vizualize_dim_red",
fluidPage(
column(width=6,
shinydashboard::box(title="PCA", width = NULL, status="success", solidHeader=TRUE,
column(6, align="left", uiOutput("feature_color")),
column(12, align="left",plotOutput("pca_plot") %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "pca_plot")
),
column(3, align="left", uiOutput("pc_select_x")),
column(3, align="left", uiOutput("pc_select_y"))),
uiOutput("color_box")),
column(width=6,
shinydashboard::box(title="UMAP", width = NULL, status="success", solidHeader=TRUE,
column(12, align="left", plotOutput("UMAP_plot") %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "umap_plot")
)),
uiOutput("tsne_box")
)
)
),
###############################################################
# 4. Consensus clustering on correlated cells
###############################################################
shinydashboard::tabItem(tabName = "cons_clustering",
fluidPage(
column(width=6,
shinydashboard::box(title=tagList(shiny::icon("cube"),"Hierarchical Clustering"),
width=NULL, status="success", solidHeader=TRUE,
column(12, align ="center", plotOutput("hc_heatmap_plot", height=500, width=500) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "correlation_clustering"))
),
shinydashboard::box(title = tagList(shiny::icon("cubes"),"Consensus Hierarchical Clustering"),
width=NULL, status="success", solidHeader=TRUE,
collapsible = TRUE, collapsed = TRUE,
column(12, align = "left", br()),
column(12, offset = 0,
div(style="display: inline-block;vertical-align:top; width: 200px;", sliderInput("maxK", "Max cluster :", min=2, max=20, value=10, step=1)),
div(style="display: inline-block;vertical-align:top; width: 25px;",HTML("<br>")),
div(style="display: inline-block;vertical-align:top; width: 200px;", sliderInput("consclust_iter", "Number of iterations:", min=10, max=1000, value=100, step=10)),
div(style="display: inline-block;vertical-align:top; width: 25px;",HTML("<br>")),
div(style="display: inline-block;vertical-align:top; width: 200px;", selectInput("clusterAlg", "Cluster Algorithm:", choices = c("Hierarchical","Partitioning Medoids","K-means"),selected = "hc")),
br()),
column(3, align="left", actionButton("do_cons_clust", "Launch Consensus Clustering"),
br()),
column(12, align = "left",
hr()),
column(12, align ="center", uiOutput("cons_corr_clust_pca_UI")),
column(12, align="left", uiOutput("cluster_consensus_plot")),
column(12,hr()),
column(12, align="left", textOutput("cluster_consensus_info")),
column(12, align="left", uiOutput("cons_clust_pdf"))
),
shinydashboard::box(title=tagList(shiny::icon("fas fa-filter"),"Filter lowly correlated cells"),
width=NULL, status="success", solidHeader=TRUE,
collapsible = TRUE, collapsed = TRUE,
column(12, align="center",
plotOutput("cell_cor_hist_plot", height=300, width=500) %>%
shinycssloaders::withSpinner(type=8,color="#0F9D58",size = 0.75) %>%
shinyhelper::helper(type = 'markdown', icon ="info-circle",
content = "filter_correlation_distrib")),
column(12, align = "left",
hr(),
sliderInput("corr_threshold", "Correlation threshold quantile:", min=75, max=99, value=99, step=1),
sliderInput("percent_correlation", "Minimum percentage of cells to correlate with (%)", min=0, max=15, value=1, step=0.25)),
column(3, align="left", br(),
actionButton("filter_corr_cells", "Filter & save")),
column(12, uiOutput("table_cor_filtered")
)
)
),
column(width=6,
shinydashboard::box(title="Select Cluster Number", width=NULL, status="success", solidHeader=TRUE,
align="left",
column(width=4,uiOutput("nclust_UI")),
column(width=3, br(),br(), checkboxInput("cluster_type",label = shiny::HTML("<b>Use consensus</b>"),value = FALSE)),
column(width=3,br(),br(),actionButton(inputId = "choose_cluster", label = "Choose Cluster"))
),
uiOutput("contingency_table_cluster"),
uiOutput("UMAP_box"),
uiOutput("tsne_box_cf"),
uiOutput("color_box_cf"),
shinydashboard::box(title="Correlation heatmap with cluster annotation", width=NULL,
status="success", solidHeader=TRUE, align="left",
column(width=4,
actionButton(inputId = "do_annotated_heatmap_plot", label = "Plot Clustered Heatmap"), br()),
column(width=12, uiOutput("annotated_heatmap_UI"))
)
)
)
),
###############################################################
# 5. Peak calling [optional]
###############################################################
shinydashboard::tabItem(tabName = "peak_calling",
fluidPage(
column(width=6,
shinydashboard::box(title="Peak calling", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", textOutput("peak_calling_info"), hr()),
tags$style(HTML(".large_icon { font-size: 70px; }")),
column(5, align="left",
htmlOutput("peak_calling_system"), hr()),
column(5,offset = 1,align="center", htmlOutput("peak_calling_icon")),
column(12, align="left",
sliderInput("peak_distance_to_merge", "Select distance of peaks to merge:", min=0, max=50000, value=5000, step=100),
shinyFiles::shinyDirButton("bam_folder", "Choose a folder containing the BAM files" ,
title = "Please select a folder:",
buttonType = "default", class = NULL), br(),
textOutput("bam_dir"), br(),
uiOutput("bam_upload")),
column(4, align="left", textOutput("pc_k_selection"),
selectInput("pc_stat","Select statistic for cutoff:", choices=c("p.value", "q.value"), selected="p.value")),
column(8, align="left", br(), br(), br(), br(),
sliderInput("pc_stat_value", "Select significance threshold:", min=0, max=0.25, value=0.05, step=0.01)),
column(12, align="left", hr(), actionButton("do_pc", "Start"))))
# ,column(width=6, uiOutput("pc_plot_box"))
)
),
###############################################################
# 6. Differential analysis
###############################################################
shinydashboard::tabItem(tabName = "diff_analysis",
fluidPage(
column(width=6,
shinydashboard::box(title="Differential Analysis parameters", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", textOutput("diff_analysis_info"), br()),
column(8, align="left", uiOutput("selected_k"), br()),
column(5, align="left", selectInput("da_method", "Select type of DA method:",
choices=list("Wilcoxon" = "wilcox",
"edgeR GLM" = "neg.binomial"))),
column(5, align="left", selectInput("de_type", "Select type of cluster comparison:", choices=c("one_vs_rest","pairwise"))),
column(12, align="left", sliderInput("qval.th", "Adjusted p-value to select significant features:", min=0.01, max=0.4, value=0.01, step=0.01),
sliderInput("cdiff.th", "Minimum log-fold change to select significant locations:", min=0, max=3, value=1, step=0.01)),
# plotOutput("distrib_norm_hist") %>% shinyhelper::helper(type = 'markdown',
# icon ="info-circle",
# content = "distrib_norm_hist"
# )),
# uiOutput("only_contrib_cell_ui")),
# column(1, align="left", br()),
# column(11, align="left", uiOutput("contrib_thresh")),
# column(1, align="left", br()),
# column(8, align="left", uiOutput("contrib_hist")),
# column(3, align="left", br(), uiOutput("contrib_info")),
column(12, align="left", hr(), actionButton("do_wilcox", "Start analysis"))),
uiOutput("da_summary_box")),
column(width=6,
uiOutput("da_visu_box")))
),
###############################################################
# 7. Enrichment analysis
###############################################################
shinydashboard::tabItem(tabName = "enrich_analysis",
fluidPage(
column(width=6,
shinydashboard::box(title="Enrichment analysis", width=NULL, status="success", solidHeader=TRUE,
column(12, align="left", htmlOutput("enr_info"), br(),
uiOutput("use_peaks"),
actionButton("do_enrich", "Start enrichment analysis"))),
shinydashboard::box(title="Enriched gene sets in differential regions across clusters", width=NULL, status="success", solidHeader=TRUE,
column(4, align="left", uiOutput("enr_clust_sel"), br()),
column(8, align="left", uiOutput("enr_class_sel"), br()),
column(12, align="left",
mainPanel(tabsetPanel(id='enr_tables',
tabPanel("In differential features", div(style = 'overflow-x: scroll', DT::dataTableOutput('all_enrich_table'))),
tabPanel("In enriched features", div(style = 'overflow-x: scroll', DT::dataTableOutput('over_enrich_table'))),
tabPanel("In depleted features", div(style = 'overflow-x: scroll', DT::dataTableOutput('under_enrich_table')))), width=12),
br(), br(), br(), br(), br(),
downloadButton("download_enr_data", "Download tables")))),
column(width=6,
shinydashboard::box(title="Enrichment near TSS", width=NULL, status="success", solidHeader=TRUE,
column(4, align="left", uiOutput("gene_sel")),
column(8, align="left", uiOutput("region_sel")),
column(12, align="left", uiOutput("gene_umap_UI")))))
),
###############################################################
# 8. Close app
###############################################################
shinydashboard::tabItem(tabName="close_and_save",
fluidPage(shinyjs::useShinyjs(),
# extendShinyjs(text = jscode, functions = c("closeWindow")),
column(width=6,
shinydashboard::box(title='Close App & Save Analysis', solidHeader=TRUE, status='danger', width=NULL,
column(12, actionButton("close_and_save", "Close App & Save Analysis")))
),
column(width=6,
shinydashboard::box(title="Delete analysis", width = NULL, status="success", solidHeader=TRUE,
column(9, align="left", uiOutput("selected_delete_analysis")),
column(3, align="left", br(), actionButton("delete_analysis", "Delete")),
column(12, align="left", textOutput("analysis_deletion_info"))))
)
)
)))
)
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