inst/sample_size_estimator/ui.R
In Vitek-Lab/MSstatsSampleSize: Simulation tool for optimal design of high-dimensional MS-based proteomics experiment
## MSstatsSampleSize Shiny UI
###############################################################
dashboardPage(
skin="black",
tags$head(
tags$style(
HTML(".shiny-notification {
height: 100px;
width: 800px;
opacity: 1;
position:fixed;
top: calc(50% - 50px);;
left: calc(55% - 400px);;
}
.shiny-output-error-validation {
color: red;
}"
)
)
),
##### Header #####
header = dashboardHeader(
title = "MSstats- Sample Size Estimator",
titleWidth = 350
),
#### SideBar ####
sidebar = dashboardSidebar(
shinyjs::useShinyjs(),
width = 250,
sidebarMenu(
id="tabs",
##### Home Tab ####
menuItem("Home", tabName = "home", icon = icon("home")),
#### Data Import Tab ####
menuItem("1: Import data", tabName = "import_data", icon = icon("file-import")),
#### Data Simulation Tab ####
menuItem("2: Simulate datasets",
tabName = "explore_simulated", icon = icon("project-diagram")),
#### Analyze Simulation Tab ####
menuItem("3: Plan experiment",
tabName = "plan_experiment", icon = icon("vial")),
br(),
br(),
br(),
downloadButton(outputId = "log_down", label = "Download Log",
icon = icon("download"),
style = "margin-top: 25px; margin-left: 25px; margin-right: 25px; color: #000000",)
)
),
##### Body ####
body = dashboardBody(
shinyjs::useShinyjs(),
tabItems(
#### Home Tab ####
tabItem(
tabName = "home",
includeMarkdown("www/Welcome.md"),
actionButton(inputId = "start_process",
label = "Start",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px')
),
#### Import Data Tab ####
tabItem(
tabName = "import_data",
navbarPage("", id = "myNavBar",
tabPanel("Import", fluidPage(
box(title = "Data Import Wizard", width = 12,
solidHeader = T, status = 'primary',
includeHTML("www/data_import.Rmd"),
fluidRow(
column(width = 4,
selectInput("data_format", "Select Data Type",
choice = FORMATS_LIST,
selected = FORMATS_LIST[2])),
column(width = 4,
fileInput("standard_count", "Select Protein Abundance File",
multiple = FALSE,
accept = EXTENSTIONS)),
column(width = 4,
fileInput("standard_annot", "Select Sample Annotation File",
multiple = FALSE,
accept = EXTENSTIONS))
),
fluidRow(
column(width = 3,
selectInput("transform", "Base for Log Transform",
choices = c("No Transform","log","log10","log2"),
selected = "No Transform"))
),
fluidRow(
column(width = 2,
actionButton("import_data", "Import dataset",
icon = icon("file-import"),
style = CSS_BUTTON_REG))
)
),
box(title = "Example Data", width = 12, solidHeader = T,
status = 'primary',
includeHTML("www/example.Rmd"))
)
),
tabPanel("Explore Data", fluidPage(
fluidRow(
column(9,
h3(textOutput("dataset_name"),
style="display: inline-block;")),
column(3,
actionButton(inputId = "nav_to_sim",
label = "Next Step",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px'))
),
br(),
#### Summary Tables ####
fluidRow(
column(width = 6,
fluidRow(width = 12,
# Data table output for summary table
box(title = "Summary", solidHeader = T,
status = "primary", width = 12,
withSpinner(DT::dataTableOutput(
"sum_table"),
proxy.height = "100px")
)
)
),
column(width = 6,
# Data table output for condition summary
fluidRow(width = 12,
box(title = "Condition Summary", solidHeader = T,
status = "primary", width = 12,
withSpinner(DT::dataTableOutput(
"cond_sum_table"),
proxy.height = "100px"))
)
),
),
br(),
#### Box plots and HeatMap ####
fluidRow(
# Box plot
box(title = "QC Box Plot", solidHeader = T, status = "primary",
width = 12,
withSpinner(plotly::plotlyOutput("global_boxplot"))
)
)
)
)
)
),
#### Data Simulation Tab #####
tabItem(
tabName = "explore_simulated", height = NULL,
fluidRow(
column(9, h1("Simulate datasets",
style="display: inline-block;")),
column(3,
shinyjs::disabled(actionButton(inputId = "nav_to_exp",
label = "Next Step",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px')))
),
##### Checkboxes for file Input and set seed options ####
fluidRow(
column(1, checkboxInput(input = "set_seed",
label = "Set Seed")),
column(1, numericInput(inputId = "seed",
label="Value", value=10,
step = 1))
),
fluidRow(
#### Box to input simulation parameters from the dashboard ######
box(id = "param_box", title = "Parameters For Simulating DataSets",
width = 5, solidHeader = T, status = "primary",
# Number of simulations
numericInput(inputId = "n_sim", label = "Number of Simulations",
value = 10, min = 10, max = 500, step = 1) %>%
shinyhelper::helper(type = "markdown", content = "n_sim"),
# number of sample to be simulated
textInput(inputId = "n_samp_grp", label = "Samples per group",
value = "5,10,20", placeholder = "5,10,20") %>%
shinyhelper::helper(type = "markdown", content = "n_samp_grp"),
# Use default fold change values?
checkboxInput(inputId = "exp_fc", label = "Use Default Fold Change",
value = T)%>%
shinyhelper::helper(type = "markdown", content = "exp_fc"),
selectInput(inputId = "b_group", label = "Baseline Group",
choices = NULL)%>%
shinyhelper::helper(type = "markdown", content = "b_group",
id = "b_group_help"),
# Render editable data.table for fold change values
DT::DTOutput('fc_values') %>%
shinyhelper::helper(type = "markdown", content = "fc_values",
id = "fc_values_help"),
br(),
# Input vector off different proteins
selectInput(inputId = "da_prots",
label = paste("How do you want to specify Differentially",
"abundant proteins ?"),
choices = c("Text Input", "Upload csv file")),
textInput(inputId = "diff_prot",
label = "List of Differential Abundant Proteins",
value = NULL,
placeholder = "List of comma separated Proteins") %>%
shinyhelper::helper(type = "markdown", content = "diff_prot",
id = "diff_prot_help"),
fileInput(inputId = "da_prots_file",
label = "DA Proteins File Upload", multiple = F,
accept = EXTENSTIONS),
selectInput(inputId = "rank_proteins", label = "Rank proteins by",
choices = c("Combined", "Mean", "SD"),
selected = "Combined"),
fluidRow(
column(width = 7,
sliderInput(inputId = "mean_ip",
label = "Mean Abundance quantile cutoff",
val = 0, min = 0, max = 100, step = 0.01,
post = '%')
),
column(width = 5,
selectInput(inputId = 'mean_equality',
label= 'Zone',
choices = c("Low","High"), selected = "High")
)
),
fluidRow(
column(width = 7,
sliderInput(inputId = "sd_ip",
label = "SD quantile cutoff",
val = 0, min = 0, max = 100, step = 0.01,
post = '%')
),
column(width = 5,
selectInput(inputId = 'sd_equality',
label = "Zone",
choice = c("Low","High"), selected = "High")
)
),
br(),
# should validation set be simulated as well?
selectInput(inputId = "sim_val", label = "Simulate Validation Set",
choices = c(T,F), selected = F) %>%
shinyhelper::helper(type = "markdown", content = "sim_val"),
# Define number of samples in the validation groups
numericInput(inputId = "n_val_samp_grp", label = "Valid samples per group",
value = 50, min = 50, max = 1000, step = 50) %>%
shinyhelper::helper(type = "markdown", content = "n_val_samp_grp",
id = "n_val_samp_grp_help"),
# Simulate the dataset provided inputs, gets enabled dynamically
shinyjs::disabled(
actionButton(inputId = "simulate", label = "Simulate Data",
icon = icon("project-diagram"),
style = CSS_BUTTON_REG))
),
column(width = 7,# heatmap
box(title = "Mean-Variance Plot", solidHeader = T,
status = "primary", width = 12,
withSpinner(plotOutput("mean_sd_plot"),
proxy.height = "200px"),
htmlOutput("adv_meansd")
)
)
),
fluidRow(
#### Simulation details section #####
box(title = "Simulated Datasets", solidHeader = T, status = "primary",
width = 12,
fluidRow(
##### Select individual simulation, previous and next buttons #####
column(4, selectInput(inputId = "simulations", label = "Simulations",
choices = NULL)),
column(2, shinyjs::disabled(actionButton(inputId = "back",
label = "Previous",
icon = icon("arrow-left"),
style = "margin-top: 25px;",
width = '100px'))),
column(2, shinyjs::disabled(actionButton(inputId = "fwd",
label = "Next",
icon = icon("arrow-right"),
style = "margin-top: 25px;",
width = '100px'))),
column(2, shinyjs::disabled(downloadButton(outputId = "download_pca",
label = "Download",
icon = icon("download"),
style = "margin-top: 25px;",
width = '150px')))
),
withSpinner(plotOutput("pca_plot", height = '600px'))
)
)
),
#### Analyse Simulation Tab ####
tabItem(
tabName = "plan_experiment",
h1("Plan Experiment"),
h3("Calculate Sample Size For Classification"),
#### Model Setup Box ####
fluidRow(
box(status = 'primary', solidHeader = T, title = "Model Setup",
width = 12,
fluidRow(
column(width = 2,
selectInput(inputId = "classifier", label = "Select Model to Train",
choice = MODELS, width = '200px')
),
column(width = 3,
checkboxGroupButtons(inputId = "checkbox_inputs",
label = "Options",
choices = c("Use h2o Package",
"Parameter Tuning"),
checkIcon = list(
yes = icon("check-square"),
no = icon("square-o")),
width = "300px")%>%
shinyhelper::helper(type = "markdown",
content = "checkbox_inputs",
id = "checkbox_inputs_help")
),
column(offset = 1, width = 1,
shinyjs::disabled(actionButton(inputId = "run_model",
label = "Run Model",
width = "100px",
style = CSS_BUTTON_RUN)),
),
column(offset= 1, width = 1,
shinyjs::disabled(downloadButton(outputId = "download_plots",
label = "Download Plots" ,
style = "margin-top:25px;",
width = "250px"))
),
column(offset=1, width = 1,
shinyjs::disabled(downloadButton(outputId ="generate_report",
label ="Generate Report",
style ="margin-top:25px;
margin-top: 25px;
display: inline-block;
color: #fff;
background-color: orange;
border-color: black;")))
),
column(width = 3,
selectInput(inputId = "stop_metric",
label = "Stopping Metric",
choices = STOPPING_METRIC) %>%
shinyhelper::helper(content = "h2o_stopping_metric",
id = "stop_metric_help"),
numericInput(inputId = "nfolds", label = "N-Folds",
value = 0, min = 0, max = 100, step = 1)%>%
shinyhelper::helper(content = "h2o_nfold",
id = "nfolds_help"),
selectInput(inputId = "f_assignment", label = "Fold Assignment",
choices = FOLD_ASSIGNMENT) %>%
shinyhelper::helper(content = "h2o_f_assignment",
id = "f_assignment_help"),
numericInput(inputId = "iters", label = "Iterations", value = 200,
min = 1, max = 1000, step = 10) %>%
shinyhelper::helper(content = "h2o_iters",
id = "iters_help"),
selectInput(inputId = "family", label = "Family", choices = FAMILY,
selected = "binomial") %>%
shinyhelper::helper(content = "h2o_family",
id = "family_help"),
sliderInput(inputId = "laplace", label = "Laplace", min = 0,
max = 1, value = 0) %>%
shinyhelper::helper(content = "h2o_laplace",
id = "laplace_help"),
numericInput(inputId = "caret_rf",
label = "Variables to Randomly Sample",
value = 2, min = 1, max = 1000, step = 1)%>%
shinyhelper::helper(content = "caret_rf",
id = "caret_rf_help")
),
column(width = 3,
selectInput(inputId = "link", label = "Link",
choices = LINK) %>%
shinyhelper::helper(content = "h2o_link",
id = "link_help"),
selectInput(inputId = "solver", label = "Solver",
choices = SOLVER) %>%
shinyhelper::helper(content = "h2o_solver",
id = "solver_help"),
sliderInput(inputId = "eps_sdev", label = "Cutoff Threshold",
min = 0, max = 1, step = 0.001, value = 0.01) %>%
shinyhelper::helper(content = "h2o_eps_sdev",
id = "eps_sdev_help"),
sliderInput(inputId = "min_sdev", label = "Minimum SD",
min = 0.01, value = 0.01, max = 1) %>%
shinyhelper::helper(content = "h2o_min_sdev",
id = "min_sdev_help"))
),
verbatimTextOutput("v3")
),
fluidRow(
##### Accuracy Box ####
box(width = 6, title = "Accuracy", status = "info", solidHeader = T,
withSpinner(plotOutput(outputId = 'acc_plot')),
verbatimTextOutput("default", placeholder = F)
),
##### Protein Importance Box ####
box(width = 6, title = "Protein Importance", status = "success",
solidHeader = T,
fluidRow(
column(width = 4,
selectInput(inputId = "s_size", label = "Sample Size",
choices = NULL)
),
shinyjs::disabled(actionButton(inputId = "back_varimp", label = "Prev.",
icon = icon("arrow-left"),
style = "margin-top: 25px;")),
shinyjs::disabled(actionButton(inputId = "fwd_varimp", label = "Next",
icon = icon("arrow-right"),
style = "margin-top: 25px;"))
),
withSpinner(plotOutput('importance_plot'))
)
)
)
)
)
)
Vitek-Lab/MSstatsSampleSize documentation built on Aug. 28, 2020, 10:39 a.m.
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## MSstatsSampleSize Shiny UI
###############################################################
dashboardPage(
skin="black",
tags$head(
tags$style(
HTML(".shiny-notification {
height: 100px;
width: 800px;
opacity: 1;
position:fixed;
top: calc(50% - 50px);;
left: calc(55% - 400px);;
}
.shiny-output-error-validation {
color: red;
}"
)
)
),
##### Header #####
header = dashboardHeader(
title = "MSstats- Sample Size Estimator",
titleWidth = 350
),
#### SideBar ####
sidebar = dashboardSidebar(
shinyjs::useShinyjs(),
width = 250,
sidebarMenu(
id="tabs",
##### Home Tab ####
menuItem("Home", tabName = "home", icon = icon("home")),
#### Data Import Tab ####
menuItem("1: Import data", tabName = "import_data", icon = icon("file-import")),
#### Data Simulation Tab ####
menuItem("2: Simulate datasets",
tabName = "explore_simulated", icon = icon("project-diagram")),
#### Analyze Simulation Tab ####
menuItem("3: Plan experiment",
tabName = "plan_experiment", icon = icon("vial")),
br(),
br(),
br(),
downloadButton(outputId = "log_down", label = "Download Log",
icon = icon("download"),
style = "margin-top: 25px; margin-left: 25px; margin-right: 25px; color: #000000",)
)
),
##### Body ####
body = dashboardBody(
shinyjs::useShinyjs(),
tabItems(
#### Home Tab ####
tabItem(
tabName = "home",
includeMarkdown("www/Welcome.md"),
actionButton(inputId = "start_process",
label = "Start",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px')
),
#### Import Data Tab ####
tabItem(
tabName = "import_data",
navbarPage("", id = "myNavBar",
tabPanel("Import", fluidPage(
box(title = "Data Import Wizard", width = 12,
solidHeader = T, status = 'primary',
includeHTML("www/data_import.Rmd"),
fluidRow(
column(width = 4,
selectInput("data_format", "Select Data Type",
choice = FORMATS_LIST,
selected = FORMATS_LIST[2])),
column(width = 4,
fileInput("standard_count", "Select Protein Abundance File",
multiple = FALSE,
accept = EXTENSTIONS)),
column(width = 4,
fileInput("standard_annot", "Select Sample Annotation File",
multiple = FALSE,
accept = EXTENSTIONS))
),
fluidRow(
column(width = 3,
selectInput("transform", "Base for Log Transform",
choices = c("No Transform","log","log10","log2"),
selected = "No Transform"))
),
fluidRow(
column(width = 2,
actionButton("import_data", "Import dataset",
icon = icon("file-import"),
style = CSS_BUTTON_REG))
)
),
box(title = "Example Data", width = 12, solidHeader = T,
status = 'primary',
includeHTML("www/example.Rmd"))
)
),
tabPanel("Explore Data", fluidPage(
fluidRow(
column(9,
h3(textOutput("dataset_name"),
style="display: inline-block;")),
column(3,
actionButton(inputId = "nav_to_sim",
label = "Next Step",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px'))
),
br(),
#### Summary Tables ####
fluidRow(
column(width = 6,
fluidRow(width = 12,
# Data table output for summary table
box(title = "Summary", solidHeader = T,
status = "primary", width = 12,
withSpinner(DT::dataTableOutput(
"sum_table"),
proxy.height = "100px")
)
)
),
column(width = 6,
# Data table output for condition summary
fluidRow(width = 12,
box(title = "Condition Summary", solidHeader = T,
status = "primary", width = 12,
withSpinner(DT::dataTableOutput(
"cond_sum_table"),
proxy.height = "100px"))
)
),
),
br(),
#### Box plots and HeatMap ####
fluidRow(
# Box plot
box(title = "QC Box Plot", solidHeader = T, status = "primary",
width = 12,
withSpinner(plotly::plotlyOutput("global_boxplot"))
)
)
)
)
)
),
#### Data Simulation Tab #####
tabItem(
tabName = "explore_simulated", height = NULL,
fluidRow(
column(9, h1("Simulate datasets",
style="display: inline-block;")),
column(3,
shinyjs::disabled(actionButton(inputId = "nav_to_exp",
label = "Next Step",
icon = icon("arrow-right"),
style = CSS_BUTTON,
width = '200px')))
),
##### Checkboxes for file Input and set seed options ####
fluidRow(
column(1, checkboxInput(input = "set_seed",
label = "Set Seed")),
column(1, numericInput(inputId = "seed",
label="Value", value=10,
step = 1))
),
fluidRow(
#### Box to input simulation parameters from the dashboard ######
box(id = "param_box", title = "Parameters For Simulating DataSets",
width = 5, solidHeader = T, status = "primary",
# Number of simulations
numericInput(inputId = "n_sim", label = "Number of Simulations",
value = 10, min = 10, max = 500, step = 1) %>%
shinyhelper::helper(type = "markdown", content = "n_sim"),
# number of sample to be simulated
textInput(inputId = "n_samp_grp", label = "Samples per group",
value = "5,10,20", placeholder = "5,10,20") %>%
shinyhelper::helper(type = "markdown", content = "n_samp_grp"),
# Use default fold change values?
checkboxInput(inputId = "exp_fc", label = "Use Default Fold Change",
value = T)%>%
shinyhelper::helper(type = "markdown", content = "exp_fc"),
selectInput(inputId = "b_group", label = "Baseline Group",
choices = NULL)%>%
shinyhelper::helper(type = "markdown", content = "b_group",
id = "b_group_help"),
# Render editable data.table for fold change values
DT::DTOutput('fc_values') %>%
shinyhelper::helper(type = "markdown", content = "fc_values",
id = "fc_values_help"),
br(),
# Input vector off different proteins
selectInput(inputId = "da_prots",
label = paste("How do you want to specify Differentially",
"abundant proteins ?"),
choices = c("Text Input", "Upload csv file")),
textInput(inputId = "diff_prot",
label = "List of Differential Abundant Proteins",
value = NULL,
placeholder = "List of comma separated Proteins") %>%
shinyhelper::helper(type = "markdown", content = "diff_prot",
id = "diff_prot_help"),
fileInput(inputId = "da_prots_file",
label = "DA Proteins File Upload", multiple = F,
accept = EXTENSTIONS),
selectInput(inputId = "rank_proteins", label = "Rank proteins by",
choices = c("Combined", "Mean", "SD"),
selected = "Combined"),
fluidRow(
column(width = 7,
sliderInput(inputId = "mean_ip",
label = "Mean Abundance quantile cutoff",
val = 0, min = 0, max = 100, step = 0.01,
post = '%')
),
column(width = 5,
selectInput(inputId = 'mean_equality',
label= 'Zone',
choices = c("Low","High"), selected = "High")
)
),
fluidRow(
column(width = 7,
sliderInput(inputId = "sd_ip",
label = "SD quantile cutoff",
val = 0, min = 0, max = 100, step = 0.01,
post = '%')
),
column(width = 5,
selectInput(inputId = 'sd_equality',
label = "Zone",
choice = c("Low","High"), selected = "High")
)
),
br(),
# should validation set be simulated as well?
selectInput(inputId = "sim_val", label = "Simulate Validation Set",
choices = c(T,F), selected = F) %>%
shinyhelper::helper(type = "markdown", content = "sim_val"),
# Define number of samples in the validation groups
numericInput(inputId = "n_val_samp_grp", label = "Valid samples per group",
value = 50, min = 50, max = 1000, step = 50) %>%
shinyhelper::helper(type = "markdown", content = "n_val_samp_grp",
id = "n_val_samp_grp_help"),
# Simulate the dataset provided inputs, gets enabled dynamically
shinyjs::disabled(
actionButton(inputId = "simulate", label = "Simulate Data",
icon = icon("project-diagram"),
style = CSS_BUTTON_REG))
),
column(width = 7,# heatmap
box(title = "Mean-Variance Plot", solidHeader = T,
status = "primary", width = 12,
withSpinner(plotOutput("mean_sd_plot"),
proxy.height = "200px"),
htmlOutput("adv_meansd")
)
)
),
fluidRow(
#### Simulation details section #####
box(title = "Simulated Datasets", solidHeader = T, status = "primary",
width = 12,
fluidRow(
##### Select individual simulation, previous and next buttons #####
column(4, selectInput(inputId = "simulations", label = "Simulations",
choices = NULL)),
column(2, shinyjs::disabled(actionButton(inputId = "back",
label = "Previous",
icon = icon("arrow-left"),
style = "margin-top: 25px;",
width = '100px'))),
column(2, shinyjs::disabled(actionButton(inputId = "fwd",
label = "Next",
icon = icon("arrow-right"),
style = "margin-top: 25px;",
width = '100px'))),
column(2, shinyjs::disabled(downloadButton(outputId = "download_pca",
label = "Download",
icon = icon("download"),
style = "margin-top: 25px;",
width = '150px')))
),
withSpinner(plotOutput("pca_plot", height = '600px'))
)
)
),
#### Analyse Simulation Tab ####
tabItem(
tabName = "plan_experiment",
h1("Plan Experiment"),
h3("Calculate Sample Size For Classification"),
#### Model Setup Box ####
fluidRow(
box(status = 'primary', solidHeader = T, title = "Model Setup",
width = 12,
fluidRow(
column(width = 2,
selectInput(inputId = "classifier", label = "Select Model to Train",
choice = MODELS, width = '200px')
),
column(width = 3,
checkboxGroupButtons(inputId = "checkbox_inputs",
label = "Options",
choices = c("Use h2o Package",
"Parameter Tuning"),
checkIcon = list(
yes = icon("check-square"),
no = icon("square-o")),
width = "300px")%>%
shinyhelper::helper(type = "markdown",
content = "checkbox_inputs",
id = "checkbox_inputs_help")
),
column(offset = 1, width = 1,
shinyjs::disabled(actionButton(inputId = "run_model",
label = "Run Model",
width = "100px",
style = CSS_BUTTON_RUN)),
),
column(offset= 1, width = 1,
shinyjs::disabled(downloadButton(outputId = "download_plots",
label = "Download Plots" ,
style = "margin-top:25px;",
width = "250px"))
),
column(offset=1, width = 1,
shinyjs::disabled(downloadButton(outputId ="generate_report",
label ="Generate Report",
style ="margin-top:25px;
margin-top: 25px;
display: inline-block;
color: #fff;
background-color: orange;
border-color: black;")))
),
column(width = 3,
selectInput(inputId = "stop_metric",
label = "Stopping Metric",
choices = STOPPING_METRIC) %>%
shinyhelper::helper(content = "h2o_stopping_metric",
id = "stop_metric_help"),
numericInput(inputId = "nfolds", label = "N-Folds",
value = 0, min = 0, max = 100, step = 1)%>%
shinyhelper::helper(content = "h2o_nfold",
id = "nfolds_help"),
selectInput(inputId = "f_assignment", label = "Fold Assignment",
choices = FOLD_ASSIGNMENT) %>%
shinyhelper::helper(content = "h2o_f_assignment",
id = "f_assignment_help"),
numericInput(inputId = "iters", label = "Iterations", value = 200,
min = 1, max = 1000, step = 10) %>%
shinyhelper::helper(content = "h2o_iters",
id = "iters_help"),
selectInput(inputId = "family", label = "Family", choices = FAMILY,
selected = "binomial") %>%
shinyhelper::helper(content = "h2o_family",
id = "family_help"),
sliderInput(inputId = "laplace", label = "Laplace", min = 0,
max = 1, value = 0) %>%
shinyhelper::helper(content = "h2o_laplace",
id = "laplace_help"),
numericInput(inputId = "caret_rf",
label = "Variables to Randomly Sample",
value = 2, min = 1, max = 1000, step = 1)%>%
shinyhelper::helper(content = "caret_rf",
id = "caret_rf_help")
),
column(width = 3,
selectInput(inputId = "link", label = "Link",
choices = LINK) %>%
shinyhelper::helper(content = "h2o_link",
id = "link_help"),
selectInput(inputId = "solver", label = "Solver",
choices = SOLVER) %>%
shinyhelper::helper(content = "h2o_solver",
id = "solver_help"),
sliderInput(inputId = "eps_sdev", label = "Cutoff Threshold",
min = 0, max = 1, step = 0.001, value = 0.01) %>%
shinyhelper::helper(content = "h2o_eps_sdev",
id = "eps_sdev_help"),
sliderInput(inputId = "min_sdev", label = "Minimum SD",
min = 0.01, value = 0.01, max = 1) %>%
shinyhelper::helper(content = "h2o_min_sdev",
id = "min_sdev_help"))
),
verbatimTextOutput("v3")
),
fluidRow(
##### Accuracy Box ####
box(width = 6, title = "Accuracy", status = "info", solidHeader = T,
withSpinner(plotOutput(outputId = 'acc_plot')),
verbatimTextOutput("default", placeholder = F)
),
##### Protein Importance Box ####
box(width = 6, title = "Protein Importance", status = "success",
solidHeader = T,
fluidRow(
column(width = 4,
selectInput(inputId = "s_size", label = "Sample Size",
choices = NULL)
),
shinyjs::disabled(actionButton(inputId = "back_varimp", label = "Prev.",
icon = icon("arrow-left"),
style = "margin-top: 25px;")),
shinyjs::disabled(actionButton(inputId = "fwd_varimp", label = "Next",
icon = icon("arrow-right"),
style = "margin-top: 25px;"))
),
withSpinner(plotOutput('importance_plot'))
)
)
)
)
)
)
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