inst/App/ui.R
In nicocriscuolo/StructuRly: A novel shiny app to produce comprehensive, detailed and interactive plots for population genetic analysis
################################### UI ########################################
ui <- fluidPage(
useShinyjs(), # Recall every function of Shinyjs in the UI
fluidRow(
column(width = 12,
p(h3(strong(em("StructuRly")),
strong("0.1.0"), "-",
"Comprehensive, detailed and interactive plots for",
a(em("STRUCTURE"),
href = "https://web.stanford.edu/group/pritchardlab/structure.html",
target = "_blank"),
"and",
a(em("ADMIXTURE"),
href = "http://software.genetics.ucla.edu/admixture/",
target = "_blank"),
"population analysis",
align = "center")
)
)
),
br(),
br(),
fluidRow(
column(width = 2,
actionButton(inputId = "import_data",
label = h4(icon(name = "upload"),
"Import the data"),
width = "100%"),
br(),
br(),
conditionalPanel(conditio = "input.import_data > 0",
radioButtons(inputId = "analysis_type",
label = h5(icon(name = "list-ul"), "Choose an action"),
choices = list("Import raw genetic data" = 1,
"Import population analysis" = 2,
"Compare partitions" = 3),
selected = 1),
conditionalPanel(condition = "input.analysis_type == 1",
fileInput(inputId = "Data_PER_Str",
label = h5(icon(name = "file"),
"Input file (.csv, .txt)"),
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
conditionalPanel(condition = "output.fileUploaded_PER",
actionButton(inputId = "check_table",
label = h4(icon(name = "check"),
"Start the analysis!"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2",
fileInput(inputId = "Data_DA_Str",
label = h5(icon(name = "file"),
"Input file (.csv, .txt, .Q)"),
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv",
".Q")
),
conditionalPanel(condition = "output.dataFormat == 'Q'",
fileInput(inputId = "FAM_file",
label = h5(icon(name = "file-alt"),
"Input information file (.fam)"),
accept = c(".fam")
)
),
conditionalPanel(condition = "output.fileUploaded_DA",
actionButton(inputId = "customize_plot",
label = h4(icon(name = "check"),
"Start the analysis!"),
width = "100%")
)
)
),
# br(),
# br(),
# br(),
# fluidRow(
# div(style = "display: inline-block;"),
# actionButton(inputId = "open_structure",
# label = h6(icon(name = "bar-chart"),
# "STRUCTURE")
# ),
# actionButton(inputId = "open_admixture",
# label = h6(icon(name = "bar-chart"),
# "ADMIXTURE")
# )
# ),
br(),
br(),
br(),
br(),
fluidRow(
column(width = 12,
align = "center",
actionButton(inputId = "back_instructions",
label = h6(icon(name = "book"),
"Instructions"),
width = "100%"
),
shinyjs::hidden(actionButton(inputId = "back_results",
label = h6(icon(name = "book"),
"StructuRly"),
width = "100%"
)
),
br(),
br(),
br(),
br(),
br(),
conditionalPanel(condition = "input.analysis_type == 1 &
input.data_per_str_panels == 'dendrogram_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_dendrogram",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 1 &
input.data_per_str_panels == 'pcoa_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_pcoa",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2 &
input.data_da_str_panels == 'barplot_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_barplot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2 &
input.data_da_str_panels == 'triangleplot_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_triangleplot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.show_comparison_outputs == 'Contingency plot'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_comparison_plot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
)
)
), # Closes input column
######################### UI DATA FOR STRUCUTRE ####
column(width = 10,
shinyjs::hidden(mainPanel(id = "instructions",
sliderInput("pipeline_slider",
label = "Instructions panel size",
min = 1000,
max = 3000,
value = 1000),
br(),
uiOutput("structurly_pipeline")
)
),
conditionalPanel(condition = "input.check_table == 0 &
input.customize_plot == 0 &
input.analysis_type != 3" ,
mainPanel(id = "wallpaper",
img(src = "Wallpaper_StructuRly.png",
height = "650px",
width = "1150px"),
br(),
a("Nicola G. Criscuolo",
href = "mailto:nico.criscuolo1618@gmail.com"),
" - Department of Environmental Systems Science, ETH Zürich, Zurich, Switzerland",
br(),
br(),
a("Claudia Angelini",
href = "mailto:c.angelini@na.iac.cnr.it"),
" - Institute for Applications of Calculus “M. Picone”, National Research Council, Naples, Italy",
br(),
br(),
"Detailed instructions of", em("StructuRly"),
"are available at the following",
a("GitHub repository",
href = "https://github.com/nicocriscuolo/StructuRly",
target = "_blank"),
br(),
br()
)
),
conditionalPanel(condition = "input.analysis_type == 1 &
input.check_table > 0",
mainPanel(id = "table_panel",
tabsetPanel(id = "data_per_str_panels",
type = "pills",
tabPanel(title = h4("Input table"),
br(),
fluidRow(
column(width = 2,
radioButtons(inputId = "separator", label = h5("Separator"),
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ",")
),
column(width = 2,
radioButtons(inputId = "quote", label = h5("Quote"),
choices = c(None = "",
Single = "'",
Double = '"'),
selected = "")
),
column(width = 4, selectInput(inputId = "subset_variable",
label = h5("Subset of the variables"),
choices = "",
multiple = TRUE),
downloadButton(outputId = "download_subset",
label = "Download subset")
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_import")
)
)
),
tabPanel(title = h4("Basic stats"),
br(),
fluidRow(
column(width = 4,
selectInput(inputId = "stats_type",
label = h5("Choose information"),
choices = "")
),
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
column(width = 3,
selectInput(inputId = "locus_name",
label = h5("Select locus"),
choices = "")
)
),
column(width = 7,
uiOutput(outputId = "hw.test_sliderInput")
)
),
br(),
fluidRow(
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
column(width = 12,
DT::dataTableOutput(outputId = "alleles_types")
)
),
conditionalPanel(condition = "input.stats_type == 'N° of different alleles per locus'",
column(width = 12,
plotlyOutput(outputId = "number_alleles_per_locus")
)
),
conditionalPanel(condition = " input.stats_type == 'Missing values per locus' || input.stats_type == 'Diversity indices'
|| input.stats_type == 'P-gen' || input.stats_type == 'H-W equilibrium'",
column(width = 8,
DT::dataTableOutput(outputId = "loci_stats")
)
)
),
br(),
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
fluidRow(
column(width = 12,
plotlyOutput(outputId = "allele_frequency")
)
)
)
),
tabPanel(title = h4("Cluster analysis"),
value = "dendrogram_panel",
br(),
fluidRow(
column(width = 2,
radioButtons(inputId = "na_value",
label = h5("NA values"),
choices = list("Zero" = "zero",
"Mean" = "mean")
)
),
column(width = 2,
radioButtons(inputId = "distance",
label = h5("Distance"),
choices = list("Binary" = "binary",
"Geometric" = "geometric")
)
),
conditionalPanel(condition = "input.distance == 'binary'",
column(width = 3,
selectInput(inputId = "similarity_coefficient",
label = h5("Similarity coefficient"),
choices = list("Jaccard Index" = 1,
"Sokal & Michener" = 2,
"Sokal & Sneath" = 3,
"Rogers & Tanimoto" = 4,
"Dice & Sorensen" = 5,
"Hamann coefficient" = 6,
"Ochiai" = 7,
"Sokal & Sneath 2" = 8,
"Phi of Pearson" = 9,
"S2 Coefficent" = 10),
selected = 1)
)
),
conditionalPanel(condition = "input.distance == 'geometric'",
column(width = 3,
selectInput(inputId = "geometric_distance",
label = h5("Geometric distance"),
choices = list("Euclidean" = "euclidean",
"Maximum" = "maximum",
"Manhattan" = "manhattan",
"Canberra" = "canberra",
"Minkowski" = "minkowski")
)
)
),
column(width = 3,
selectInput(inputId = "hierarchical_method",
label = h5("Method"),
choices = list("Complete" = "complete",
"Single" = "single",
"Ward" = "ward.D",
"Ward - 2" = "ward.D2",
"UPGMA" = "average",
"WPGMA" = "mcquitty",
"Median" = "median",
"UPGMC" = "centroid"))
),
column(width = 2,
numericInput(inputId = "cluster_count",
label = h5("Cluster count"),
value = 1,
min = 1, max = 20)
)
),
fluidRow(
column(width = 5
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "dendrogram_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "dendrogram_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_dendrogram",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "dendrogram_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "dendrogram_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "dendrogram_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "dendrogram_leaves_size",
label = h5("Leaves size"),
min = 1,
max = 10,
value = 4,
step = 0.5)
),
column(width = 3,
sliderInput(inputId = "dendrogram_leaves_angle",
label = h5("Leaves angle"),
min = 0,
max = 90,
value = 90)
),
column(width = 3,
sliderInput(inputId = "dendrogram_y_label_size",
label = h5("Y labels size"),
min = 10,
max = 20,
value = 12)
),
column(width = 3,
sliderInput(inputId = "dendrogram_branches_width",
label = h5("Branches width"),
min = 0.1,
max = 2,
value = 0.6)
)
),
br(),
fluidRow(
column(width = 12,
plotOutput(outputId = "tree",
width = "1100px",
height = "550px")
)
),
br()
),
tabPanel(value = "pcoa_panel",
title = h4("PCoA"),
br(),
fluidRow(
# column(width = 3,
# radioButtons(inputId = "pcoa_na_value",
# label = h5("NA values"),
# choices = c("Zero",
# "Mean",
# "Remove samples"),
# selected = "Mean")
# ),
column(width = 3,
selectInput(inputId = "pcoa_dissimilarity_indices",
label = h5("Dissimilarity indices"),
choices = list("Euclidean" = "euclidean",
"Manhattan" = "manhattan",
"Canberra" = "canberra",
"Clark" = "clark",
"Bray" = "bray",
"Kulczynski" = "kulczynski",
"Jaccard" = "jaccard",
"Gower" = "gower",
"Morisita" = "morisita",
"Horn" = "horn",
"Raup" = "raup",
"Binomial" = "binomial",
"Cao" = "cao",
"Mahalanobis" = "mahalanobis"),
selected = "euclidean")
),
column(width = 2,
radioButtons(inputId = "pcoa_colours",
label = h5("Dots colour"),
choices = c("Default",
"Gray scale"),
selected = "Default")
),
conditionalPanel(condition = "input.pcoa_colours == 'Default'",
column(width = 2,
h5("Resampling"),
actionButton(inputId = "resample_pcoa_default_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
conditionalPanel(condition = "input.pcoa_colours == 'Gray scale'",
column(width = 2,
h5("Resampling"),
actionButton(inputId = "resample_pcoa_gray_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
column(width = 1
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "pcoa_plot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_pcoa_plot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "pcoa_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "pcoa_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "pcoa_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "pcoa_x_label_size",
label = h5("X labels size"),
min = 1,
max = 15,
value = 9)
),
column(width = 3,
sliderInput(inputId = "pcoa_y_label_size",
label = h5("Y labels size"),
min = 1,
max = 15,
value = 9)
),
column(width = 3,
sliderInput(inputId = "pcoa_dots_size",
label = h5("Dots size"),
min = 0.5,
max = 10,
value = 2,
step = 0.5)
),
column(width = 3,
sliderInput(inputId = "pcoa_axis_title_size",
label = h5("Titles size"),
min = 1,
max = 15,
value = 9)
)
),
fluidRow(
column(width = 12,
plotlyOutput(outputId = "pcoa_plot",
width = "1110px",
height = "500px")
)
)
),
tabPanel(title = h4("STRUCTURE input table"),
br(),
fluidRow(
column(width = 2,
h5("Individuals ID"),
verbatimTextOutput(outputId = "individuals_ID"
)
),
column(width = 2,
h5("Populations ID"),
verbatimTextOutput(outputId = "populations_ID"
)
),
column(width = 2,
h5("Locations ID"),
verbatimTextOutput(outputId = "locations_ID"
)
),
column(width = 2,
h5("Individuals"),
verbatimTextOutput(outputId = "individuals_number")
),
column(width = 2,
h5("Loci"),
verbatimTextOutput(outputId = "loci_number")
),
column(width = 2,
h5("Ploidy"),
verbatimTextOutput(outputId = "ploidy")
)
),
fluidRow(
conditionalPanel(condition = "output.individuals_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_ID",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.individuals_ID == 'NO'",
column(width = 2
)
),
conditionalPanel(condition = "output.populations_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_POP",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.populations_ID == 'NO'",
column(width = 2
)
),
conditionalPanel(condition = "output.locations_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_LOC",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.locations_ID == 'NO'",
column(width = 2
)
),
column(width = 3,
offset = 3,
downloadButton(outputId = "download",
label = "Download the table")
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_export")
)
)
)
)
)),
####################### UI DATA FROM STRUCUTRE ####
conditionalPanel(condition = "input.analysis_type == 2 &
input.customize_plot > 0",
mainPanel(id = "plot_panel",
tabsetPanel(id = "data_da_str_panels",
type = "pills",
tabPanel(title = h4("Input table"),
br(),
conditionalPanel(condition = "output.dataFormat != 'Q'",
fluidRow(
column(width = 2,
radioButtons(inputId = "separator2", label = h5("Separator"),
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ",")
),
column(width = 2,
radioButtons(inputId = "quote2", label = h5("Quote"),
choices = c(None = "",
Single = "'",
Double = '"'),
selected = "")
)
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_import2")
)
)
),
tabPanel(value = "barplot_panel",
title = h4("Barplot"),
br(),
fluidRow(
column(width = 1,
h5("K"),
verbatimTextOutput(outputId = "cluster_number")
),
column(width = 2,
h5("Order"),
radioButtons(inputId = "sort",
label = NULL,
choices = c("Original" = "original",
"Sort by Q" = "Q",
"Alphabetic" = "alphabetic"),
selected = "original")
),
column(width = 2,
h5("Bar position"),
radioButtons(inputId = "barpos",
label = NULL,
choices = c("Stack" = "stack",
"Dodge" = "dodge"),
selected = "stack"
)
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "barplot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "barplot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_barplot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "barplot_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "barplot_height",
label = NULL,
value = 570,
min = 200,
max = 2000
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "barplot_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "x_label_size",
label = h5("X labels size"),
min = 1,
max = 10,
value = 5)
),
column(width = 3,
sliderInput(inputId = "y_label_size",
label = h5("Y labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "x_label_angle",
label = h5("X labels angle"),
min = 0,
max = 90,
value = 90)
),
column(width = 3,
sliderInput(inputId = "axis_title_size",
label = h5("Titles size"),
min = 1,
max = 10,
value = 5)
)
),
fluidRow(
column(width = 3,
radioButtons(inputId = "barplot_colours_vector",
label = "Colours palette",
choices = c("Customized",
"Gray scale"),
selected = "Customized")
),
conditionalPanel(condition = "input.barplot_colours_vector == 'Gray scale'",
column(width = 4,
h5("Resampling"),
actionButton(inputId = "resample_gray_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 1",
colourpicker::colourInput(inputId = "colour_1",
label = h5("K 1"),
value = "#FF5733",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 2",
colourpicker::colourInput(inputId = "colour_2",
label = h5("K 2"),
value = "#A4F771",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 3",
colourpicker::colourInput(inputId = "colour_3",
label = h5("K 3"),
value = "#71F7EF",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >=4",
colourpicker::colourInput(inputId = "colour_4",
label = h5("K 4"),
value = "#EEC764",
showColour = "background",
allowTransparent = TRUE)
)
)
),
column(width = 2,
uiOutput(outputId = "show_location_marks")
),
column(width = 3,
selectInput(inputId = "group_barplot_by",
label = h5("Group by"),
choices = "")
)
),
fluidRow(
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 5",
colourpicker::colourInput(inputId = "colour_5",
label = h5("K 5"),
value = "#EDA590",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 6",
colourpicker::colourInput(inputId = "colour_6",
label = h5("K 6"),
value = "#74AA8A",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 7",
colourpicker::colourInput(inputId = "colour_7",
label = h5("K 7"),
value = "#337489",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 8",
colourpicker::colourInput(inputId = "colour_8",
label = h5("K 8"),
value = "#9972A4",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 9",
colourpicker::colourInput(inputId = "colour_9",
label = h5("K 9"),
value = "#F1F359",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 10",
colourpicker::colourInput(inputId = "colour_10",
label = h5("K 10"),
value = "#FAB86D",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 11",
colourpicker::colourInput(inputId = "colour_11",
label = h5("K 11"),
value = "#D6FFD6",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 12",
colourpicker::colourInput(inputId = "colour_12",
label = h5("K 12"),
value = "#F1CBF1",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 13",
colourpicker::colourInput(inputId = "colour_13",
label = h5("K 13"),
value = "#FFF000",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 14",
colourpicker::colourInput(inputId = "colour_14",
label = h5("K 14"),
value = "#8CE0F0",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 15",
colourpicker::colourInput(inputId = "colour_15",
label = h5("K 15"),
value = "#ACE4BD",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 16",
colourpicker::colourInput(inputId = "colour_16",
label = h5("K 16"),
value = "#C6BF47",
showColour = "background",
allowTransparent = TRUE)
)
)
)
),
fluidRow(
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 17",
colourpicker::colourInput(inputId = "colour_17",
label = h5("K 17"),
value = "#24941C",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 18",
colourpicker::colourInput(inputId = "colour_18",
label = h5("K 18"),
value = "#57BFFE",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 19",
colourpicker::colourInput(inputId = "colour_19",
label = h5("K 19"),
value = "#D96492",
showColour = "background",
allowTransparent = TRUE)
)
),
fluidRow(
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 20",
colourpicker::colourInput(inputId = "colour_20",
label = h5("K 20"),
value = "#9E7183",
showColour = "background",
allowTransparent = TRUE)
)
)
)
)
),
fluidRow(
column(width = 12,
plotlyOutput(outputId = "structure_plot",
height = "600px")
)
)
),
tabPanel(value = "triangleplot_panel",
title = h4("Triangle plot"),
br(),
fluidRow(
column(width = 1,
h5("K"),
verbatimTextOutput(outputId = "cluster_number_2")
),
column(width = 2,
h5("Bottom left"),
selectInput(inputId = "bottom_left",
label = NULL,
choices = "")
),
column(width = 2,
h5("Bottom right"),
selectInput(inputId = "bottom_right",
label = NULL,
choices = "")
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "triangleplot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "triangleplot_format",
label = NULL,
choices = list(".pdf" = ".pdf",
".jpeg" = ".jpeg",
".png" = ".png",
".svg" = ".svg"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_triangleplot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "triangleplot_width",
label = NULL,
value = 600,
min = 250,
max = 1000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "triangleplot_height",
label = NULL,
value = 600,
min = 250,
max = 1000
)
),
column(width = 4,
h5("Symbol size"),
sliderInput(inputId = "triangleplot_symbol_size",
label = NULL,
value = 8,
min = 1,
max = 20
)
)
),
fluidRow(
column(width = 12, align = "center",
plotlyOutput(outputId = "triangle_plot",
height = "550px"
)
)
)
)
),
br(),
br(),
br()
)
),
####################### COMPARING PARTITIONS ####
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table == 0 &
input.customize_plot == 0",
mainPanel(id = "comparison_1",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
# Controllare se funziona quando si importano nuovi dataset dopo i primi importati e
# non sono più disponibili i bottoni "Start the analysis"
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table > 0 &
input.customize_plot == 0",
mainPanel(id = "comparison_2",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table == 0 &
input.customize_plot > 0",
mainPanel(id = "comparison_3",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table > 0 &
input.customize_plot > 0",
mainPanel(id = "comparison_true",
fluidRow(
column(width = 2,
h5("Hierarchic"),
verbatimTextOutput(outputId = "Cluster_hclust")
),
column(width = 2,
h5("Pop analysis"),
verbatimTextOutput(outputId = "Cluster_STR")
),
column(width = 3,
h5("Agr. index"),
selectInput(inputId = "agreement_index",
label = NULL,
choices = list("Rand Index" = "rand",
"Adj. Rand Index" = "crand"))
),
column(width = 2,
h5("Agr. value"),
verbatimTextOutput(outputId = "agreement_value")
),
column(width = 3,
h5("Comparison outputs"),
selectInput(inputId = "show_comparison_outputs",
label = NULL,
choices = c("Table",
"Contingency table",
"Contingency plot"))
)
),
br(),
conditionalPanel(condition = "input.show_comparison_outputs == 'Table'",
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "comparison_table")
)
)
),
conditionalPanel(condition = "input.show_comparison_outputs == 'Contingency table'",
fluidRow(
column(width = 12,
column(width = 12,
verbatimTextOutput(outputId = "contingency_table")
)
)
)
),
conditionalPanel(condition = "input.show_comparison_outputs == 'Contingency plot'",
fluidRow(
column(width = 5),
column(width = 3,
h5("Plot title"),
textInput(inputId = "comparison_plot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "comparison_plot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_comparison_plot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "comparison_plot_width",
label = NULL,
value = 950,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "comparison_plot_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "comparison_plot_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
br(),
fluidRow(
column(width = 3,
sliderInput(inputId = "comp_x_label_size",
label = h5("X labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "comp_y_label_size",
label = h5("Y labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "comp_label_angle",
label = h5("Labels angle"),
min = 0,
max = 90,
value = 0)
),
column(width = 3,
sliderInput(inputId = "comp_axis_title_size",
label = h5("Titles size"),
min = 1,
max = 10,
value = 5)
)
),
br(),
fluidRow(
column(width = 3
),
column(width = 9,
fluidRow(style = "height:250px;",
plotlyOutput(outputId = "barplot_cluster_hierarchical")
)
)
),
fluidRow(
column(width = 3,
plotlyOutput(outputId = "barplot_cluster_pop_analysis")
),
column(width = 9,
plotlyOutput(outputId = "comparison_plot")
)
)
)
)
)
) # Closes output column
)
) # Closes fluidPage
nicocriscuolo/StructuRly documentation built on April 22, 2021, 9:37 a.m.
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################################### UI ########################################
ui <- fluidPage(
useShinyjs(), # Recall every function of Shinyjs in the UI
fluidRow(
column(width = 12,
p(h3(strong(em("StructuRly")),
strong("0.1.0"), "-",
"Comprehensive, detailed and interactive plots for",
a(em("STRUCTURE"),
href = "https://web.stanford.edu/group/pritchardlab/structure.html",
target = "_blank"),
"and",
a(em("ADMIXTURE"),
href = "http://software.genetics.ucla.edu/admixture/",
target = "_blank"),
"population analysis",
align = "center")
)
)
),
br(),
br(),
fluidRow(
column(width = 2,
actionButton(inputId = "import_data",
label = h4(icon(name = "upload"),
"Import the data"),
width = "100%"),
br(),
br(),
conditionalPanel(conditio = "input.import_data > 0",
radioButtons(inputId = "analysis_type",
label = h5(icon(name = "list-ul"), "Choose an action"),
choices = list("Import raw genetic data" = 1,
"Import population analysis" = 2,
"Compare partitions" = 3),
selected = 1),
conditionalPanel(condition = "input.analysis_type == 1",
fileInput(inputId = "Data_PER_Str",
label = h5(icon(name = "file"),
"Input file (.csv, .txt)"),
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
conditionalPanel(condition = "output.fileUploaded_PER",
actionButton(inputId = "check_table",
label = h4(icon(name = "check"),
"Start the analysis!"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2",
fileInput(inputId = "Data_DA_Str",
label = h5(icon(name = "file"),
"Input file (.csv, .txt, .Q)"),
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv",
".Q")
),
conditionalPanel(condition = "output.dataFormat == 'Q'",
fileInput(inputId = "FAM_file",
label = h5(icon(name = "file-alt"),
"Input information file (.fam)"),
accept = c(".fam")
)
),
conditionalPanel(condition = "output.fileUploaded_DA",
actionButton(inputId = "customize_plot",
label = h4(icon(name = "check"),
"Start the analysis!"),
width = "100%")
)
)
),
# br(),
# br(),
# br(),
# fluidRow(
# div(style = "display: inline-block;"),
# actionButton(inputId = "open_structure",
# label = h6(icon(name = "bar-chart"),
# "STRUCTURE")
# ),
# actionButton(inputId = "open_admixture",
# label = h6(icon(name = "bar-chart"),
# "ADMIXTURE")
# )
# ),
br(),
br(),
br(),
br(),
fluidRow(
column(width = 12,
align = "center",
actionButton(inputId = "back_instructions",
label = h6(icon(name = "book"),
"Instructions"),
width = "100%"
),
shinyjs::hidden(actionButton(inputId = "back_results",
label = h6(icon(name = "book"),
"StructuRly"),
width = "100%"
)
),
br(),
br(),
br(),
br(),
br(),
conditionalPanel(condition = "input.analysis_type == 1 &
input.data_per_str_panels == 'dendrogram_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_dendrogram",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 1 &
input.data_per_str_panels == 'pcoa_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_pcoa",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2 &
input.data_da_str_panels == 'barplot_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_barplot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 2 &
input.data_da_str_panels == 'triangleplot_panel'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_triangleplot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.show_comparison_outputs == 'Contingency plot'",
withBusyIndicatorUI(
actionButton(inputId = "show_r_code_comparison_plot",
label = h6(icon(name = "download"),
"Download R Code"),
width = "100%")
)
),
)
)
), # Closes input column
######################### UI DATA FOR STRUCUTRE ####
column(width = 10,
shinyjs::hidden(mainPanel(id = "instructions",
sliderInput("pipeline_slider",
label = "Instructions panel size",
min = 1000,
max = 3000,
value = 1000),
br(),
uiOutput("structurly_pipeline")
)
),
conditionalPanel(condition = "input.check_table == 0 &
input.customize_plot == 0 &
input.analysis_type != 3" ,
mainPanel(id = "wallpaper",
img(src = "Wallpaper_StructuRly.png",
height = "650px",
width = "1150px"),
br(),
a("Nicola G. Criscuolo",
href = "mailto:nico.criscuolo1618@gmail.com"),
" - Department of Environmental Systems Science, ETH Zürich, Zurich, Switzerland",
br(),
br(),
a("Claudia Angelini",
href = "mailto:c.angelini@na.iac.cnr.it"),
" - Institute for Applications of Calculus “M. Picone”, National Research Council, Naples, Italy",
br(),
br(),
"Detailed instructions of", em("StructuRly"),
"are available at the following",
a("GitHub repository",
href = "https://github.com/nicocriscuolo/StructuRly",
target = "_blank"),
br(),
br()
)
),
conditionalPanel(condition = "input.analysis_type == 1 &
input.check_table > 0",
mainPanel(id = "table_panel",
tabsetPanel(id = "data_per_str_panels",
type = "pills",
tabPanel(title = h4("Input table"),
br(),
fluidRow(
column(width = 2,
radioButtons(inputId = "separator", label = h5("Separator"),
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ",")
),
column(width = 2,
radioButtons(inputId = "quote", label = h5("Quote"),
choices = c(None = "",
Single = "'",
Double = '"'),
selected = "")
),
column(width = 4, selectInput(inputId = "subset_variable",
label = h5("Subset of the variables"),
choices = "",
multiple = TRUE),
downloadButton(outputId = "download_subset",
label = "Download subset")
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_import")
)
)
),
tabPanel(title = h4("Basic stats"),
br(),
fluidRow(
column(width = 4,
selectInput(inputId = "stats_type",
label = h5("Choose information"),
choices = "")
),
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
column(width = 3,
selectInput(inputId = "locus_name",
label = h5("Select locus"),
choices = "")
)
),
column(width = 7,
uiOutput(outputId = "hw.test_sliderInput")
)
),
br(),
fluidRow(
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
column(width = 12,
DT::dataTableOutput(outputId = "alleles_types")
)
),
conditionalPanel(condition = "input.stats_type == 'N° of different alleles per locus'",
column(width = 12,
plotlyOutput(outputId = "number_alleles_per_locus")
)
),
conditionalPanel(condition = " input.stats_type == 'Missing values per locus' || input.stats_type == 'Diversity indices'
|| input.stats_type == 'P-gen' || input.stats_type == 'H-W equilibrium'",
column(width = 8,
DT::dataTableOutput(outputId = "loci_stats")
)
)
),
br(),
conditionalPanel(condition = "input.stats_type == 'Types of different alleles'",
fluidRow(
column(width = 12,
plotlyOutput(outputId = "allele_frequency")
)
)
)
),
tabPanel(title = h4("Cluster analysis"),
value = "dendrogram_panel",
br(),
fluidRow(
column(width = 2,
radioButtons(inputId = "na_value",
label = h5("NA values"),
choices = list("Zero" = "zero",
"Mean" = "mean")
)
),
column(width = 2,
radioButtons(inputId = "distance",
label = h5("Distance"),
choices = list("Binary" = "binary",
"Geometric" = "geometric")
)
),
conditionalPanel(condition = "input.distance == 'binary'",
column(width = 3,
selectInput(inputId = "similarity_coefficient",
label = h5("Similarity coefficient"),
choices = list("Jaccard Index" = 1,
"Sokal & Michener" = 2,
"Sokal & Sneath" = 3,
"Rogers & Tanimoto" = 4,
"Dice & Sorensen" = 5,
"Hamann coefficient" = 6,
"Ochiai" = 7,
"Sokal & Sneath 2" = 8,
"Phi of Pearson" = 9,
"S2 Coefficent" = 10),
selected = 1)
)
),
conditionalPanel(condition = "input.distance == 'geometric'",
column(width = 3,
selectInput(inputId = "geometric_distance",
label = h5("Geometric distance"),
choices = list("Euclidean" = "euclidean",
"Maximum" = "maximum",
"Manhattan" = "manhattan",
"Canberra" = "canberra",
"Minkowski" = "minkowski")
)
)
),
column(width = 3,
selectInput(inputId = "hierarchical_method",
label = h5("Method"),
choices = list("Complete" = "complete",
"Single" = "single",
"Ward" = "ward.D",
"Ward - 2" = "ward.D2",
"UPGMA" = "average",
"WPGMA" = "mcquitty",
"Median" = "median",
"UPGMC" = "centroid"))
),
column(width = 2,
numericInput(inputId = "cluster_count",
label = h5("Cluster count"),
value = 1,
min = 1, max = 20)
)
),
fluidRow(
column(width = 5
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "dendrogram_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "dendrogram_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_dendrogram",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "dendrogram_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "dendrogram_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "dendrogram_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "dendrogram_leaves_size",
label = h5("Leaves size"),
min = 1,
max = 10,
value = 4,
step = 0.5)
),
column(width = 3,
sliderInput(inputId = "dendrogram_leaves_angle",
label = h5("Leaves angle"),
min = 0,
max = 90,
value = 90)
),
column(width = 3,
sliderInput(inputId = "dendrogram_y_label_size",
label = h5("Y labels size"),
min = 10,
max = 20,
value = 12)
),
column(width = 3,
sliderInput(inputId = "dendrogram_branches_width",
label = h5("Branches width"),
min = 0.1,
max = 2,
value = 0.6)
)
),
br(),
fluidRow(
column(width = 12,
plotOutput(outputId = "tree",
width = "1100px",
height = "550px")
)
),
br()
),
tabPanel(value = "pcoa_panel",
title = h4("PCoA"),
br(),
fluidRow(
# column(width = 3,
# radioButtons(inputId = "pcoa_na_value",
# label = h5("NA values"),
# choices = c("Zero",
# "Mean",
# "Remove samples"),
# selected = "Mean")
# ),
column(width = 3,
selectInput(inputId = "pcoa_dissimilarity_indices",
label = h5("Dissimilarity indices"),
choices = list("Euclidean" = "euclidean",
"Manhattan" = "manhattan",
"Canberra" = "canberra",
"Clark" = "clark",
"Bray" = "bray",
"Kulczynski" = "kulczynski",
"Jaccard" = "jaccard",
"Gower" = "gower",
"Morisita" = "morisita",
"Horn" = "horn",
"Raup" = "raup",
"Binomial" = "binomial",
"Cao" = "cao",
"Mahalanobis" = "mahalanobis"),
selected = "euclidean")
),
column(width = 2,
radioButtons(inputId = "pcoa_colours",
label = h5("Dots colour"),
choices = c("Default",
"Gray scale"),
selected = "Default")
),
conditionalPanel(condition = "input.pcoa_colours == 'Default'",
column(width = 2,
h5("Resampling"),
actionButton(inputId = "resample_pcoa_default_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
conditionalPanel(condition = "input.pcoa_colours == 'Gray scale'",
column(width = 2,
h5("Resampling"),
actionButton(inputId = "resample_pcoa_gray_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
column(width = 1
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "pcoa_plot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_pcoa_plot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "pcoa_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "pcoa_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "pcoa_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "pcoa_x_label_size",
label = h5("X labels size"),
min = 1,
max = 15,
value = 9)
),
column(width = 3,
sliderInput(inputId = "pcoa_y_label_size",
label = h5("Y labels size"),
min = 1,
max = 15,
value = 9)
),
column(width = 3,
sliderInput(inputId = "pcoa_dots_size",
label = h5("Dots size"),
min = 0.5,
max = 10,
value = 2,
step = 0.5)
),
column(width = 3,
sliderInput(inputId = "pcoa_axis_title_size",
label = h5("Titles size"),
min = 1,
max = 15,
value = 9)
)
),
fluidRow(
column(width = 12,
plotlyOutput(outputId = "pcoa_plot",
width = "1110px",
height = "500px")
)
)
),
tabPanel(title = h4("STRUCTURE input table"),
br(),
fluidRow(
column(width = 2,
h5("Individuals ID"),
verbatimTextOutput(outputId = "individuals_ID"
)
),
column(width = 2,
h5("Populations ID"),
verbatimTextOutput(outputId = "populations_ID"
)
),
column(width = 2,
h5("Locations ID"),
verbatimTextOutput(outputId = "locations_ID"
)
),
column(width = 2,
h5("Individuals"),
verbatimTextOutput(outputId = "individuals_number")
),
column(width = 2,
h5("Loci"),
verbatimTextOutput(outputId = "loci_number")
),
column(width = 2,
h5("Ploidy"),
verbatimTextOutput(outputId = "ploidy")
)
),
fluidRow(
conditionalPanel(condition = "output.individuals_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_ID",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.individuals_ID == 'NO'",
column(width = 2
)
),
conditionalPanel(condition = "output.populations_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_POP",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.populations_ID == 'NO'",
column(width = 2
)
),
conditionalPanel(condition = "output.locations_ID == 'YES'",
column(width = 2,
checkboxInput(inputId = "remove_LOC",
label = "Remove",
value = FALSE)
)
),
conditionalPanel(condition = "output.locations_ID == 'NO'",
column(width = 2
)
),
column(width = 3,
offset = 3,
downloadButton(outputId = "download",
label = "Download the table")
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_export")
)
)
)
)
)),
####################### UI DATA FROM STRUCUTRE ####
conditionalPanel(condition = "input.analysis_type == 2 &
input.customize_plot > 0",
mainPanel(id = "plot_panel",
tabsetPanel(id = "data_da_str_panels",
type = "pills",
tabPanel(title = h4("Input table"),
br(),
conditionalPanel(condition = "output.dataFormat != 'Q'",
fluidRow(
column(width = 2,
radioButtons(inputId = "separator2", label = h5("Separator"),
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ",")
),
column(width = 2,
radioButtons(inputId = "quote2", label = h5("Quote"),
choices = c(None = "",
Single = "'",
Double = '"'),
selected = "")
)
)
),
br(),
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "table_import2")
)
)
),
tabPanel(value = "barplot_panel",
title = h4("Barplot"),
br(),
fluidRow(
column(width = 1,
h5("K"),
verbatimTextOutput(outputId = "cluster_number")
),
column(width = 2,
h5("Order"),
radioButtons(inputId = "sort",
label = NULL,
choices = c("Original" = "original",
"Sort by Q" = "Q",
"Alphabetic" = "alphabetic"),
selected = "original")
),
column(width = 2,
h5("Bar position"),
radioButtons(inputId = "barpos",
label = NULL,
choices = c("Stack" = "stack",
"Dodge" = "dodge"),
selected = "stack"
)
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "barplot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "barplot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_barplot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "barplot_width",
label = NULL,
value = 1000,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "barplot_height",
label = NULL,
value = 570,
min = 200,
max = 2000
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "barplot_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
fluidRow(
column(width = 3,
sliderInput(inputId = "x_label_size",
label = h5("X labels size"),
min = 1,
max = 10,
value = 5)
),
column(width = 3,
sliderInput(inputId = "y_label_size",
label = h5("Y labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "x_label_angle",
label = h5("X labels angle"),
min = 0,
max = 90,
value = 90)
),
column(width = 3,
sliderInput(inputId = "axis_title_size",
label = h5("Titles size"),
min = 1,
max = 10,
value = 5)
)
),
fluidRow(
column(width = 3,
radioButtons(inputId = "barplot_colours_vector",
label = "Colours palette",
choices = c("Customized",
"Gray scale"),
selected = "Customized")
),
conditionalPanel(condition = "input.barplot_colours_vector == 'Gray scale'",
column(width = 4,
h5("Resampling"),
actionButton(inputId = "resample_gray_scale",
label = div(icon(name = "sync-alt",
lib = "font-awesome"),
"Colors"))
)
),
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 1",
colourpicker::colourInput(inputId = "colour_1",
label = h5("K 1"),
value = "#FF5733",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 2",
colourpicker::colourInput(inputId = "colour_2",
label = h5("K 2"),
value = "#A4F771",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 3",
colourpicker::colourInput(inputId = "colour_3",
label = h5("K 3"),
value = "#71F7EF",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >=4",
colourpicker::colourInput(inputId = "colour_4",
label = h5("K 4"),
value = "#EEC764",
showColour = "background",
allowTransparent = TRUE)
)
)
),
column(width = 2,
uiOutput(outputId = "show_location_marks")
),
column(width = 3,
selectInput(inputId = "group_barplot_by",
label = h5("Group by"),
choices = "")
)
),
fluidRow(
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 5",
colourpicker::colourInput(inputId = "colour_5",
label = h5("K 5"),
value = "#EDA590",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 6",
colourpicker::colourInput(inputId = "colour_6",
label = h5("K 6"),
value = "#74AA8A",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 7",
colourpicker::colourInput(inputId = "colour_7",
label = h5("K 7"),
value = "#337489",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 8",
colourpicker::colourInput(inputId = "colour_8",
label = h5("K 8"),
value = "#9972A4",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 9",
colourpicker::colourInput(inputId = "colour_9",
label = h5("K 9"),
value = "#F1F359",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 10",
colourpicker::colourInput(inputId = "colour_10",
label = h5("K 10"),
value = "#FAB86D",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 11",
colourpicker::colourInput(inputId = "colour_11",
label = h5("K 11"),
value = "#D6FFD6",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 12",
colourpicker::colourInput(inputId = "colour_12",
label = h5("K 12"),
value = "#F1CBF1",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 13",
colourpicker::colourInput(inputId = "colour_13",
label = h5("K 13"),
value = "#FFF000",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 14",
colourpicker::colourInput(inputId = "colour_14",
label = h5("K 14"),
value = "#8CE0F0",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 15",
colourpicker::colourInput(inputId = "colour_15",
label = h5("K 15"),
value = "#ACE4BD",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 16",
colourpicker::colourInput(inputId = "colour_16",
label = h5("K 16"),
value = "#C6BF47",
showColour = "background",
allowTransparent = TRUE)
)
)
)
),
fluidRow(
conditionalPanel(condition = "input.barplot_colours_vector == 'Customized'",
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 17",
colourpicker::colourInput(inputId = "colour_17",
label = h5("K 17"),
value = "#24941C",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 18",
colourpicker::colourInput(inputId = "colour_18",
label = h5("K 18"),
value = "#57BFFE",
showColour = "background",
allowTransparent = TRUE)
)
),
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 19",
colourpicker::colourInput(inputId = "colour_19",
label = h5("K 19"),
value = "#D96492",
showColour = "background",
allowTransparent = TRUE)
)
),
fluidRow(
column(width = 1,
conditionalPanel(condition = "output.cluster_number >= 20",
colourpicker::colourInput(inputId = "colour_20",
label = h5("K 20"),
value = "#9E7183",
showColour = "background",
allowTransparent = TRUE)
)
)
)
)
),
fluidRow(
column(width = 12,
plotlyOutput(outputId = "structure_plot",
height = "600px")
)
)
),
tabPanel(value = "triangleplot_panel",
title = h4("Triangle plot"),
br(),
fluidRow(
column(width = 1,
h5("K"),
verbatimTextOutput(outputId = "cluster_number_2")
),
column(width = 2,
h5("Bottom left"),
selectInput(inputId = "bottom_left",
label = NULL,
choices = "")
),
column(width = 2,
h5("Bottom right"),
selectInput(inputId = "bottom_right",
label = NULL,
choices = "")
),
column(width = 3,
h5("Plot title"),
textInput(inputId = "triangleplot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "triangleplot_format",
label = NULL,
choices = list(".pdf" = ".pdf",
".jpeg" = ".jpeg",
".png" = ".png",
".svg" = ".svg"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_triangleplot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "triangleplot_width",
label = NULL,
value = 600,
min = 250,
max = 1000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "triangleplot_height",
label = NULL,
value = 600,
min = 250,
max = 1000
)
),
column(width = 4,
h5("Symbol size"),
sliderInput(inputId = "triangleplot_symbol_size",
label = NULL,
value = 8,
min = 1,
max = 20
)
)
),
fluidRow(
column(width = 12, align = "center",
plotlyOutput(outputId = "triangle_plot",
height = "550px"
)
)
)
)
),
br(),
br(),
br()
)
),
####################### COMPARING PARTITIONS ####
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table == 0 &
input.customize_plot == 0",
mainPanel(id = "comparison_1",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
# Controllare se funziona quando si importano nuovi dataset dopo i primi importati e
# non sono più disponibili i bottoni "Start the analysis"
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table > 0 &
input.customize_plot == 0",
mainPanel(id = "comparison_2",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table == 0 &
input.customize_plot > 0",
mainPanel(id = "comparison_3",
img(src = "Instructions_comparison.png",
width = "1100px",
height = "619px")
)
),
conditionalPanel(condition = "input.analysis_type == 3 &
input.check_table > 0 &
input.customize_plot > 0",
mainPanel(id = "comparison_true",
fluidRow(
column(width = 2,
h5("Hierarchic"),
verbatimTextOutput(outputId = "Cluster_hclust")
),
column(width = 2,
h5("Pop analysis"),
verbatimTextOutput(outputId = "Cluster_STR")
),
column(width = 3,
h5("Agr. index"),
selectInput(inputId = "agreement_index",
label = NULL,
choices = list("Rand Index" = "rand",
"Adj. Rand Index" = "crand"))
),
column(width = 2,
h5("Agr. value"),
verbatimTextOutput(outputId = "agreement_value")
),
column(width = 3,
h5("Comparison outputs"),
selectInput(inputId = "show_comparison_outputs",
label = NULL,
choices = c("Table",
"Contingency table",
"Contingency plot"))
)
),
br(),
conditionalPanel(condition = "input.show_comparison_outputs == 'Table'",
fluidRow(
column(width = 12,
DT::dataTableOutput(outputId = "comparison_table")
)
)
),
conditionalPanel(condition = "input.show_comparison_outputs == 'Contingency table'",
fluidRow(
column(width = 12,
column(width = 12,
verbatimTextOutput(outputId = "contingency_table")
)
)
)
),
conditionalPanel(condition = "input.show_comparison_outputs == 'Contingency plot'",
fluidRow(
column(width = 5),
column(width = 3,
h5("Plot title"),
textInput(inputId = "comparison_plot_title",
label = NULL,
value = "")
),
column(width = 2,
h5("Image format"),
selectInput(inputId = "comparison_plot_format",
label = NULL,
choices = list(".bmp" = ".bmp",
".jpeg" = ".jpeg",
".png" = ".png",
".tiff" = ".tiff",
".pdf" = ".pdf",
".svg" = ".svg",
".eps" = ".eps"),
selected = ".jpeg")
),
column(width = 2,
h5("Plot"),
downloadButton(outputId = "download_comparison_plot",
label = "Download")
)
),
fluidRow(
column(width = 4,
h5("Plot width"),
sliderInput(inputId = "comparison_plot_width",
label = NULL,
value = 950,
min = 500,
max = 6000
)
),
column(width = 4,
h5("Plot height"),
sliderInput(inputId = "comparison_plot_height",
label = NULL,
value = 570,
min = 200,
max = 900
)
),
column(width = 4,
h5("Plot resolution"),
sliderInput(inputId = "comparison_plot_resolution",
label = NULL,
value = 300,
min = 100,
max = 600)
)
),
br(),
fluidRow(
column(width = 3,
sliderInput(inputId = "comp_x_label_size",
label = h5("X labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "comp_y_label_size",
label = h5("Y labels size"),
min = 1,
max = 10,
value = 8)
),
column(width = 3,
sliderInput(inputId = "comp_label_angle",
label = h5("Labels angle"),
min = 0,
max = 90,
value = 0)
),
column(width = 3,
sliderInput(inputId = "comp_axis_title_size",
label = h5("Titles size"),
min = 1,
max = 10,
value = 5)
)
),
br(),
fluidRow(
column(width = 3
),
column(width = 9,
fluidRow(style = "height:250px;",
plotlyOutput(outputId = "barplot_cluster_hierarchical")
)
)
),
fluidRow(
column(width = 3,
plotlyOutput(outputId = "barplot_cluster_pop_analysis")
),
column(width = 9,
plotlyOutput(outputId = "comparison_plot")
)
)
)
)
)
) # Closes output column
)
) # Closes fluidPage
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