inst/ui.R
In UMCUGenetics/MetaboShiny: Interactive Direct Infusion Metabolomics Analysis and Annotation
shiny::fluidPage(theme = "metaboshiny.css",
class="hidden",id="metshi",
ECharts2Shiny::loadEChartsLibrary(),
shinyalert::useShinyalert(),
shinyjs::useShinyjs(),
tags$head(tags$script(src="cursor.js")),
shiny::div(style = 'position: absolute;
left: 79%;
top: 1%;',
class = "plus",
shiny::img(src="metshi_gemmo.png",
id="metshiGem",
style='position: relative;
height: 100px;
top: 7%;
left: 88%;
z-index: 1005;'),
shiny::div(id="heartHolder",
style="left: 22%;
bottom: 4%;
position: relative;",
MetaboShiny::fadeImageButton("fancy",
img.path="metshi_heart.png",
value = F)
)
),
shinyjs::extendShinyjs(text = "shinyjs.closeWindow = function() { window.close(); }",
functions = c("closeWindow")),
shiny::div(id="loading-page",
style="position: fixed;
width: 200%;
height: 200%;
z-index: 4000;
background-color: black;
opacity: 0.6;
margin-left: -20px;",
div(id="load-img-holder",
class="imagetop",
style="left: 25%;
position: absolute;
top: 25%;
height:100px;
width:100px;
margin-top: -60px;
margin-left: -60px;",
div(id="loading-bg",
style="background-image: url(metshi_heart_bezel.png);
width:120px;
height:100px;")#,
# div(id="loading-fg",
# style="background-image: url(metshi_heart_full.png);
# z-index:4001;
# width:120px;
# transition: 1s height;
# height:0px;
# margin-top: -100px;")
)
),
shiny::div(
shiny::navbarPage(windowTitle='MetaboShiny',
# use this for title
# https://codepen.io/maxspeicher/pen/zrVKLE
title=shiny::div(id="appHeader",
class="outlined",
"MetaboShiny"), # make it use the sparkle.js for unnecessary sparkle effects ;)
id="nav_general",
# this tab shows the available databases, if they are installed, and buttons to install them. generated as output$db_build_ui in 'server'
shiny::tabPanel("database", icon = shiny::icon("database",
class = "outlined"),
value="database",
shiny::fluidRow(align="center", shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Settings"), value="panel4",
shiny::sliderInput(inputId = "db_mz_range", label = "What mass range can your machine detect?",
min = 0, max = 3000, value = c(60, 600),
step = 1,post = "m/z",dragRange = TRUE),
shiny::tags$i("Warning: increasing the upper m/z boundary may drastically increase database build times
- calculating isotopes is more time-consuming for larger molecules!"),
shiny::radioButtons("db_build_mode", label = "Build base database, extended (isotopes+adducts) or both?",
choices = c("base","extended","both"),selected = "both"),
shiny::tags$i("For example: if you only defined a new adduct, pick 'extended' as the source database doesn't change."),
shiny::helpText("Include minor isotopes?"),
shinyWidgets::switchInput(
inputId = "db_all_iso",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = T
),
shiny::helpText("Include heavy C, N, O count info for each isotope?"),
shinyWidgets::switchInput(
inputId = "db_count_iso",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = F
),
shiny::helpText("Queue multiple DB builds?"),
shinyWidgets::switchInput(
inputId = "db_build_multi",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = F
),
shiny::conditionalPanel("input.db_build_multi == true",
shiny::actionButton("db_build_sel_all",
label = "Select all"),
shiny::actionButton("db_build_multi_all",
label = "Build selected DBs",
icon=shiny::icon("wrench")))
)
)),
shiny::uiOutput("db_build_ui")
),
shiny::tabPanel("data import", icon = shiny::icon("upload", class = "outlined"),
# === NEW ===
shiny::fluidRow(align="center",
shiny::column(4,
shiny::icon("signature", class = "fa-8x"),
shiny::textInput("proj_name_new", label = "STEP 1: What is your project name?", value = ""),
shiny::icon("object-group", class = "fa-8x"),
br(),
br(),
shiny::tags$b("STEP 2: Click buttons to select files"),
br(),
br(),
div(shiny::uiOutput("wipe_regex_ui"), style='font-size:70%'),
shiny::fileInput(inputId = "metadata", "Select metadata", buttonLabel="Browse",accept = c(".csv",".tsv")),
#shinyFiles::shinyFilesButton('metadata', 'metadata', 'Select metadata', FALSE),
br(),
shinyWidgets::checkboxGroupButtons(
inputId = "ms_modes",
label = "Mass spec modes:",
choices = c(`<b class='fa fa-plus'> positive</b>` = "pos",
`<b class='fa fa-minus'> negative</b>` = "neg"),
selected = c("pos","neg"),
justified = F
),
shiny::uiOutput("outlist_pickers"),
shiny::div(shiny::imageOutput("proj_merge_check"), style="height:70px")),
shiny::column(4,
shiny::icon("bullseye", class = "fa-8x"),
shiny::numericInput("ppm", "STEP 3: What level accuracy does your mass spectrometer have?",min = 0.01,max = 50,value = 3),
shiny::helpText("Round m/z values based on ppm error?"),
shinyWidgets::switchInput(
inputId = "roundMz",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::icon("star-half-alt", class = "fa-8x"),
shinyWidgets::sliderTextInput("perc_limit_samp","STEP 4: What percentage missing m/z for a sample is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=100, grid = T)),
shiny::column(4,
shiny::icon("user-check", class = "fa-8x"),
shinyWidgets::sliderTextInput("perc_limit_mz","STEP 5: What percentage missing samples for a m/z value is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=80, grid = T),
shinyWidgets::actionBttn("checkMiss", label = "Check distribution (recommended)",size = "xs"),
shiny::plotOutput("missMzPlot"),
shiny::uiOutput("missMzRatio")
)),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::tags$b("STEP 6: Convert to input-ready format"),
shiny::br(),shiny::br(),
shinyWidgets::circleButton("create_csv", icon = shiny::icon("long-arrow-alt-right", class = "fa-2x"), size = "lg")),
shiny::fluidRow(align="center",
shiny::imageOutput("proj_csv_check", inline=T),shiny::br(),shiny::br(),
shiny::tags$b("STEP 7: If "), shiny::icon("check-circle"), shiny::tags$b(" continue to normalization"),
)
),
# this tab is used to perform normalization of your data. settings are processed as input$filt_type etc. in 'server'.
tabPanel("normalize", icon = shiny::icon("shower",class = "outlined"), value="filter",
shiny::fluidRow(align="center",shiny::column(3,
shiny::selectizeInput(width = "80%",'samp_var', 'Which variable represents sample amount/concentration?', choices = c(" ")), #TODO: only show this when normalize by sample specific factor (specnorm) is selected
shiny::selectizeInput('batch_var', 'What are your batch variables?', choices = c("batch"), multiple=TRUE, options = list(maxItems = 2L)),
shiny::selectizeInput(inputId = "batch_method_a",
label = "Batch correction method if machine batch and injection order are present:",
choices = list("WaveICA - WaveICA" = "waveica",
"BatchCorrMetabolomics - batchCorr" = "batchCorr",
"limma - removeBatchEffect" = "limma",
"ComBat" = "combat",
"CovBat" = "covbat"),
selected="waveica"),
shiny::selectizeInput(inputId = "batch_method_b",
label = "Batch correction method for other variables",
choices = list("limma - removeBatchEffect" = "limma",
"ComBat" = "combat",
"CovBat" = "covbat"),
selected="combat"),
shiny::actionButton("check_csv", "Get options", icon=shiny::icon("refresh")),
shiny::hr(),
shiny::selectizeInput(width = "80%",'filt_type', 'How will you filter your m/z values?', choices = list("Interquantile range" = "iqr",
"Relative stdev" = "rsd",
"Non-parametric relative stdev" = "nrsd",
"Mean" = "mean",
"Standard deviation" = "sd",
"Median absolute deviation" = "mad",
"Median" = "median",
"None" = "none"),
selected = "none"),
shiny::conditionalPanel("input.filt_type != 'none'",
shiny::numericInput(inputId="maxMz",
label = "Max. m/z to keep",
value = 5000)
),
shiny::selectizeInput(width = "80%",'norm_type', 'What type of normalization do you want to do?', choices = list("Quantile normalization" = "QuantileNorm",
"QCs per batch normalization" = "QcNorm",
"By reference feature" = "ProbNorm",
"By reference compound" = "CompNorm",
"By sample specific factor" = "SpecNorm",
"Sum" = "SumNorm",
"Median" = "MedianNorm",
"None" = "NULL"),
selected="QuantileNorm"),
# ref 289.18874-
shiny::conditionalPanel("input.norm_type == 'ProbNorm'",
div(shinyWidgets::pickerInput(
inputId = "ref_mz",
label = div(icon("search"), style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "click below button",
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker"),
shiny::actionButton("check_ref_mzs", "Get options", icon=shiny::icon("refresh"))
),
shiny::selectizeInput(width = "80%",'trans_type', 'How will you transform your data?', choices = list("Log transform" = "LogNorm",
"Cubic root transform" = "CrNorm",
"None" = "NULL"),
selected="LogNorm"),
shiny::selectizeInput(width = "80%",'scale_type', 'How will you scale your data?', choices = list("Autoscale/Z-transform" = "AutoNorm",
"Mean-center" = "MeanCenter",
"Pareto Scaling" = "ParetoNorm",
"Range scaling" = "RangeNorm",
"None" = "NULL"),
selected="AutoNorm"),
shinyWidgets::sliderTextInput("miss_perc_2","What percentage missing samples for a m/z is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=20, grid = T),
shiny::selectizeInput(width = "80%",'miss_type', 'How to deal with missing values?', choices = list("Half feature minimum" = "colmin",
"Half sample minimum" = "rowmin",
"Total minimum" = "min",
"Random forest" = "rf",
#"Impute w/ regression" = "regr",
"KNN imputation" = "knn",
"SVD imputation" = "svdImpute",
"BPCA imputation" = "bpca",
"PPCA imputation" = "ppca",
"Median" = "median",
"Mean" = "mean",
"Leave them out" = "exclude",
"Leave them alone" = "none"),
selected = "rowmin"),
shiny::conditionalPanel("input.miss_type == 'rf'",
shinyWidgets::switchInput("rf_norm_method", label = "Method:",
value = TRUE, onLabel = "missRanger",
offLabel="missForest",size = "small"),
shiny::sliderInput("rf_norm_ntree", label = "Trees built per variable", value = 10, min = 1, max = 50, step=1),
#numericInput("rf_norm_mtry", label = "Trees built per variable", value = 10, min = 1, max = 50)
shiny::radioButtons("rf_norm_parallel", label = "Parallelize?", choices = list("no",
"forests",
"variables"),
selected = "variables")
),
shinyWidgets::switchInput(
inputId = "redo_upon_change",
value = TRUE,
label = "Renormalize after subsetting?:",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
# - - - - - -
shinyWidgets::switchInput(
inputId = "pca_corr",
value = FALSE,
label = "PCA correction",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::conditionalPanel("input.pca_corr == true",
sliderInput("keep_pcs", label = h3("Keep variance in PCs:"), min = 0,
max = 300, value = c(10, 50))
),
MetaboShiny::switchButton(inputId = "remove_outliers",
label = "Exclude outliers?",
value = FALSE, col = "BW", type = "YN"),
shiny::actionButton("initialize", "Go", icon=shiny::icon("hand-o-right")),
br(),br(),br(),br()
), shiny::column(9,
# show the summary plots post-normalization
shiny::tabsetPanel(tabPanel("m/z values",# icon=shiny::icon("braille"),
shiny::fluidRow(shiny::column(6,
shiny::imageOutput("empty2",width="100%",height="1px"),
shiny::uiOutput("var1_wrap")),
shiny::column(6,
shiny::uiOutput("var3_wrap"))),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("var2_wrap")),
shiny::column(6,
shiny::uiOutput("var4_wrap")))
),
shiny::tabPanel("samples",# icon=shiny::icon("tint"),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("samp1_wrap")),
shiny::column(6,
shiny::uiOutput("samp3_wrap"))),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("samp2_wrap")),
shiny::column(6,
shiny::uiOutput("samp4_wrap")))
)
)
)
)),
shiny::tabPanel("prematch", icon = shiny::icon("search", class = "outlined"), value = "prematch",
# - - - pre-matching part - - -
shiny::fluidRow(align="center",
MetaboShiny::switchButton(inputId = "do_prematch",
label = "Do matching beforehand?",
col = "BW",
type = "YN"),
shiny::tags$i("All m/z values will be searched in the databases of choice and the results will be saved to your save file for fast access."),shiny::br(),
shiny::tags$i("Search results can still be overridden by manual searching. Don't forget to save after!")),
shiny::br(),
shiny::fluidRow(align="center",
shiny::column(2),
shiny::column(8, shiny::conditionalPanel("input.do_prematch == true",
shiny::h2("Included databases:"),
shiny::uiOutput("db_prematch_select"),
shinyWidgets::circleButton("select_db_prematch_all",
icon = shiny::icon("shopping-cart"),
size = "default")),
shiny::hr(),
shiny::fluidRow(shiny::column(6,shiny::h2("Find matches"),
shinyWidgets::circleButton(inputId = "prematch",
icon = shiny::icon("searchengin"))),
shiny::column(6,shiny::h2("Clear matches"),
shinyWidgets::circleButton(inputId = "clear_prematch",
icon = shiny::icon("trash"))))
),
shiny::column(2)
)),
# this tab is the main analysis tab. all tabs for all analyses are listed here, but the visibility is changed depending on the current experiment
shiny::tabPanel("analyse", icon = shiny::icon("bar-chart",class = "outlined"), value = "analysis",
div(id="panelContainer",sidebarLayout(position="right",
mainPanel = #shinyjqui::jqui_resizable(
mainPanel(width = 9, id="mainPanel",
shiny::fluidRow(align="center",
shiny::imageOutput("empty3",width="100%",height="1px"),
shinyBS::bsCollapse(id = "collapse_summary",
shinyBS::bsCollapsePanel(title = tags$b(icon("caret-down"), "show/hide selected m/z abundance", icon("caret-down")),
style = "info",
shiny::uiOutput("summary_plot_wrap"))
)),
shiny::tabsetPanel(id="statistics", selected = "inf",
# TODO: T-SNE
# this tab shows general information, mostly a message with 'please give me some data' :-)
shiny::tabPanel("start", icon = shiny::icon("star", "fa-2x"), value = "inf",
shiny::fluidRow(align="center", shiny::column(width=12,
shiny::br(),shiny::br(),shiny::br(),shiny::br(),
#shiny::hr(),
#shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"),
shiny::br(),shiny::br(),
shiny::h2("Please select a variable of interest in the sidebar!"),shiny::br(),
shiny::icon("exchange", "fa-4x"),
shiny::h2("Alternatively, load an existing dataset from the bottom toolbar."),shiny::br(),
shiny::icon("folder-open", "fa-4x"),
shiny::br(),shiny::br(),shiny::br()
#shiny::hr()
#shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg")
))),
shiny::navbarMenu("dimension reduction", icon=icon("cube", "fa-2x"),menuName = "dimred",
shiny::tabPanel("pca", value = "pca",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id = "collapse_pca",
shinyBS::bsCollapsePanel(title = h2("settings"),
value = "collapse_pca_settings",
shinyWidgets::radioGroupButtons("pca_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
shinyWidgets::actionBttn(
inputId = "do_pca",
label = "click to start PCA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_pca_plots",
shiny::tabsetPanel(shiny::tabPanel("samples",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_pca_wrap")
))),
shiny::tabPanel("loadings",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_pca_loadings_wrap"))
))),
fluidRow(align="center",
br(),
shinyWidgets::switchInput(
inputId = "pca_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "pca_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("pca_x", label = "X axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
},
selected = 1,width="80%")),
column(4,shiny::selectizeInput("pca_y", label = "Y axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("pca_z", label = "Z axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
}, selected = 3,width="80%")))
)),
shinyBS::bsCollapsePanel(title = h2("tables"),value = "collapse_pca_tables",shiny::tabsetPanel(id="pca_2",
shiny::tabPanel(title="table",
shiny::div(DT::dataTableOutput('pca_tab',width="100%"),style='font-size:80%')),
shiny::tabPanel(title="scree",
shiny::uiOutput("pca_scree_wrap")
),
shiny::tabPanel(title="loadings",
shiny::div(DT::dataTableOutput('pca_load_tab',width="100%"),style='font-size:80%'))
)),open = 1)
)
),
shiny::tabPanel("pls-da", value = "plsda",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_plsda",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_plsda_settings",
shiny::fluidRow(align = "center",
shiny::div(style="display:inline-block",
shiny::selectizeInput("plsda_type",
label="Type:",
choices=list("Normal" = "normal")
#,
# "Orthogonal" = "ortho",
# "Sparse" = "sparse")
,width = '100px',
selected=1)),br(),
shinyWidgets::actionBttn(
inputId = "do_plsda",
label = "click to start PLS-DA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_plsda_plots",
shiny::tabsetPanel(shiny::tabPanel("samples",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_plsda_wrap")))),
shiny::tabPanel("loadings",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_plsda_loadings_wrap")
))),
shiny::tabPanel("performance",
shiny::tabsetPanel(id="plsda_2",
shiny::tabPanel(title="cross-validation",
shiny::uiOutput("plsda_cv_plot_wrap")),
shiny::tabPanel(title="permutation",
shiny::uiOutput("plsda_perm_plot_wrap")))
)),
fluidRow(align="center",
br(),
shinyWidgets::switchInput(
inputId = "plsda_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "plsda_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("plsda_x", label = "X axis:", choices =
{
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("plsda_y", label = "Y axis:", choices = {
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("plsda_z", label = "Z axis:", choices = {
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_plsda_tables",
shiny::tabPanel(title="scree",
shiny::div(DT::dataTableOutput('plsda_tab',width="100%"),style='font-size:80%')),
shiny::tabPanel(title="loadings",
shiny::div(DT::dataTableOutput('plsda_load_tab',width="100%"),style='font-size:80%')))
))
),
shiny::tabPanel("t-sne", value = "tsne",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_tsne",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_tsne_settings",
shinyWidgets::radioGroupButtons("tsne_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
numericInput("tsne_dims", "Initial dimensions:", min = 5, step = 1, value = 30),
numericInput("tsne_perplex", "Perplexity:", min = 5, value = 30),
numericInput("tsne_maxiter", "Max iterations:", min = 10, value = 100),
shinyWidgets::actionBttn(
inputId = "do_tsne",
label = "click to start t-SNE",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_tsne_plots",
shiny::uiOutput("tsne_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "tsne_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "tsne_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("tsne_x", label = "X axis:", choices =
{
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("tsne_y", label = "Y axis:", choices = {
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("tsne_z", label = "Z axis:", choices = {
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
),
shiny::tabPanel("ica", value = "ica",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_ica",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_ica_settings",
shinyWidgets::radioGroupButtons("ica_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
numericInput("ica_ncomp", "Components calculated:", min = 2, step = 1, value = 3),
numericInput("ica_maxiter", "Max iterations:", min = 10, value = 100),
shinyWidgets::radioGroupButtons(
inputId = "ica_method",
label = "Method:",
choices = c("fast",
"imax", "jade"
),
justified = TRUE,selected="fast",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"))
),
shinyWidgets::actionBttn(
inputId = "do_ica",
label = "click to start ICA (independant component analysis)",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_ica_plots",
shiny::uiOutput("ica_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "ica_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "ica_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("ica_x", label = "X axis:", choices =
{
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("ica_y", label = "Y axis:", choices = {
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("ica_z", label = "Z axis:", choices = {
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
),
shiny::tabPanel("umap", value = "umap",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_umap",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_umap_settings",
shinyWidgets::radioGroupButtons("umap_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
sliderInput("umap_ncomp", "Components calculated:", min = 2, max = 20, step = 1, value = 3),
numericInput("umap_maxiter", "Max iterations:", min = 10, value = 100),
numericInput("umap_neighbors", "Neighbors used", value = 15),
shinyWidgets::actionBttn(
inputId = "do_umap",
label = "click to start UMAP",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_umap_plots",
shiny::uiOutput("umap_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "umap_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "umap_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("umap_x", label = "X axis:", choices =
{
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("umap_y", label = "Y axis:", choices = {
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("umap_z", label = "Z axis:", choices = {
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
)
),
shiny::navbarMenu("per m/z", icon=shiny::icon("fingerprint", "fa-2x"), menuName = "permz",
shiny::tabPanel("t-test", value="tt",
shiny::fluidRow(align="center",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_tt",
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_tt_settings",
MetaboShiny::switchButton("tt_nonpar", "Non-parametric?", col="BW", type="YN", value = T),
MetaboShiny::switchButton("tt_eqvar", "Equal variance?", col="BW", type="YN", value = T),
shiny::selectInput("tt_multi_test", "Multiple testing correction method:",
choices = list("Holm"="holm",
"Hochmerg"="hochberg",
"Hommel"="hommel",
"Bonferroni"="bonferroni",
"Benjamini & Hochberg"="fdr",
"Benjamini & Yekutieli"="BY",
"none"),
selected = "fdr"),
shiny::numericInput("tt_p_thresh",
label = "Maximum p-value after multiple testing:",
value=0.05,max = 1, min=0),
shinyWidgets::actionBttn(
inputId = "do_tt",
label = "click to start t-test",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_tt_plots",
shiny::uiOutput("tt_plot_wrap"),
shiny::sliderInput('tt_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_tt_tables",
shiny::div(DT::dataTableOutput('tt_tab',width="100%"),style='font-size:80%')
))
)
)),
shiny::tabPanel("anova", value="aov",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_aov",
multiple = T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_aov_settings",
shinyWidgets::actionBttn(
inputId = "do_aov",
label = "click to start ANOVA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_aov_plots",
shiny::uiOutput("aov_plot_wrap"),
shiny::sliderInput('aov_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_aov_tables",
shiny::div(DT::dataTableOutput('aov_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("fold-change", value="fc",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_fc",multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_fc_settings",
shiny::sliderInput("fc_thresh", "Fold-change threshold:",
min=0,
max=10,
value = 1.2,
step = 0.1),
shinyWidgets::actionBttn(
inputId = "do_fc",
label = "click to start fold-change analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_fc_plots",
shiny::uiOutput("fc_plot_wrap"),
shiny::sliderInput('fc_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_fc_tables",
shiny::div(DT::dataTableOutput('fc_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("meba", value="meba",
shiny::fluidRow(align="center",shinyBS::bsCollapse(id="collapse_meba", multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_meba_settings",
shinyWidgets::actionBttn(
inputId = "do_meba",
label = "click to start MEBA analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_meba_plots",
shiny::uiOutput("meba_plot_wrap"),
shiny::sliderInput('meba_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_meba_tables",
shiny::div(DT::dataTableOutput('meba_tab', width="100%"),style='font-size:80%')
)
)
)
),
shiny::tabPanel("asca", value="asca",
shiny::fluidRow(align="center",shinyBS::bsCollapse(id="collapse_asca", multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_asca_settings",
shinyWidgets::actionBttn(
inputId = "do_asca",
label = "click to start ASCA analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_asca_plots",
shiny::uiOutput("asca_plot_wrap")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_asca_tables",
shiny::div(DT::dataTableOutput('asca_tab', width="100%"),style='font-size:80%')
)
)
)
),
shiny::tabPanel("pattern", value="corr",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_corr",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_corr_settings",
uiOutput('jqui_ui'), br(),
shiny::selectizeInput("corr_corr",
"Correlation metric:",
choices = c("pearson", "spearman", "kendall"),
selected = "spearman"),
# corr_p_thresh corr_r_thresh
shiny::numericInput("corr_p_thresh",
label = "Maximum p-value:",
value=0.1),
shiny::numericInput("corr_r_thresh",
label = "Minimum correlation (absolute):",
value=0.1),
shinyWidgets::actionBttn(
inputId = "do_corr",
label = "click to start pattern finding",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_corr_plots",
shiny::uiOutput("corr_plot_wrap"),
shiny::sliderInput('corr_topn',label = "Show top:",min = 5,max=200,value = 20)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_corr_tables",
shiny::div(DT::dataTableOutput('corr_tab',width="100%"),style='font-size:80%')
))
)
)
),
shiny::navbarMenu("overview analyses", icon=shiny::icon("globe", "fa-2x"), menuName = "overview",
shiny::tabPanel("intersection plot", value="combi",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T, id="collapse_combi",
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_combi_settings",
shiny::fluidRow(align="center",
column(6, shiny::selectizeInput("combi_anal1",label = "X-axis:", choices=c()),
shiny::uiOutput("combi_anal1_picker"),
shiny::selectizeInput("combi_anal1_trans",label = "Transformation:", choices=c(
"none",
"log10",
"-log10",
"abs"
),selected = "none")
),
column(6, shiny::selectizeInput("combi_anal2",label = "Y-axis:", choices=c()),
shiny::uiOutput("combi_anal2_picker"),
shiny::selectizeInput("combi_anal2_trans",label = "Transformation:", choices=c(
"none",
"log10",
"-log10",
"abs"
),selected = "none"))
),
shinyWidgets::actionBttn(
inputId = "do_combi",
label = "click to make combi plot",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_combi_plots",
shiny::uiOutput("combi_plot_wrap")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_combi_tables",
shiny::div(DT::dataTableOutput('combi_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("heatmap", value="heatmap",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_heatmap_settings",
shiny::selectizeInput("heattable",
"Use which analysis?",
choices = c("none available"),
selected = 1,
multiple = F),
MetaboShiny::switchButton("heatsign", label = "Only significant hits?", col = "GB", type = "YN"),
MetaboShiny::switchButton("heatlimits", label = "Color based on -all- metabolites?", col = "GB", type = "YN"),
shinyWidgets::radioGroupButtons("heatmap_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
shinyWidgets::actionBttn(
inputId = "do_heatmap",
label = "click to make heatmap",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_heatmap_plots",
shiny::verbatimTextOutput("heatmap_now", placeholder = F),
shiny::uiOutput("heatmap_plot_wrap"),
shiny::sliderInput("heatmap_topn",
label = "Show top:",
min = 10,
max = 5000,
step=10,
value=20)
))
)
),
shiny::tabPanel("network", value="network",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),
value="collapse_network_settings",
shinyWidgets::switchInput("network_sel",
"Include",
value = TRUE,
onLabel="all",
offLabel="subset"),
shiny::conditionalPanel("input.network_sel == false",
shiny::selectizeInput("network_table",
"Use which analysis?",
choices = c("none available"),
selected = 1,
multiple = F),
shiny::sliderInput("network_topn",
label = "Use top m/z:",
min = 10,
max = 5000,
step=10,
value=20)
),
shiny::numericInput("network_sign",
label = "p-value threshhold",
value = 0.05,
min = 0.0000001,
max = 1),
shinyWidgets::switchInput("network_auto",
"Network style",value = T,
onLabel = "auto",
offLabel = "choose"),
shiny::conditionalPanel("input.network_auto == false",
shiny::selectizeInput("network_style", "Style:",
choices = list("Hierarchical" = "hierarchical",
"Circular" = "layout_in_circle",
"Nicely" = "layout_nicely",
"Sugiyama" = "layout_with_sugiyama",
"Star" = "layout_as_star",
"Tree" = "layout_as_tree",
"Grid" = "layout_on_grid",
"Sphere" = "layout_on_sphere",
"Randomly" = "layout_randomly",
"DH" = "layout_with_dh",
"FR" = "layout_with_fr",
"Gem" = "layout_with_gem",
"Graphopt" = "layout_with_graphopt",
"KK" = "layout_with_kk",
"LGL" = "layout_with_lgl",
"MDS" = "layout_with_mds"
))),
shiny::selectizeInput("network_corr",
label = "Correlation method:",
choices = c("pearson", "kendall", "spearman"),
multiple = F,
selected = "pearson"
),
shinyWidgets::actionBttn(
inputId = "do_network",
label = "click to make network",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_network_plots",
shiny::verbatimTextOutput("network_now", placeholder = F),
shiny::tabsetPanel(id="network_results",
shiny::tabPanel(title = "network",value = "network",
icon=shiny::icon("project-diagram"),
shiny::fluidRow(align="center",shiny::uiOutput("network_wrap")),
),
shiny::tabPanel(title = "heatmap",value = "heatmap",
icon=shiny::icon("th"),
shiny::fluidRow(align="center",shiny::uiOutput("network_heatmap_wrap")),
))
))
)
),
# this tab is used to find overlapping features of interest between analyses
# TODO: enable this with multiple saved mSets in mSet$storage
shiny::tabPanel(title="venn", value="venn", #icon=shiny::icon("comments"),
br(),
sidebarLayout(position = "left",
sidebarPanel = shiny::sidebarPanel(width = 4,
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_unselected'),style='font-size:80%'), align="center"),
shiny::fluidRow(shinyWidgets::circleButton("venn_add", icon=shiny::icon("arrow-down"), size="sm"),
shinyWidgets::circleButton("venn_remove", icon=shiny::icon("arrow-up"), size="sm"),
align="center"),
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_selected'),style='font-size:80%'),align="center"),
shiny::hr(),
shiny::selectizeInput("venn_filter_mode",label = "Use top hits or an absolute threshold?",
choices = c("top", "threshold"),selected = "top"),
shiny::conditionalPanel("input.venn_filter_mode == 'threshold'",
shiny::uiOutput("venn_threshold_ui")
),
shiny::conditionalPanel("input.venn_filter_mode == 'top'",
shiny::fluidRow(
shiny::sliderInput("venn_tophits", label = "Only include top:", min = 1, max = 200, post = " hits", value=20)
,align="center")),
shinyWidgets::switchInput(
inputId = "venn_plot_mode",
value = FALSE,
label = "Plot type",
onLabel = "upset",
offLabel = "venn",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::fluidRow(
shinyWidgets::actionBttn(
inputId = "venn_build",
label = "click to make venn diagram",
style = "bordered",
icon = icon("terminal"),
size = "sm"
),align="center")
),
mainPanel = mainPanel(
shiny::hr(),
shiny::uiOutput("venn_plot_wrap"),
# find the overlapping compounds between the groups you want to compare (user select)
# TODO: enable this with clicking the numbers/areas
shiny::fluidRow(shiny::selectizeInput(width = "80%","intersect_venn", label = "Show hits from (only):", selected = 1,choices = "",multiple = T),
align="center"),
shiny::fluidRow(shiny::uiOutput("venn_pval"), align="center"),
shiny::br(),
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_tab'),style='font-size:80%'),
align="center")
))
),
shiny::tabPanel("power calculation", value="power",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_power",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_power_settings",
shiny::sliderInput("power_nsamp",
label = "Up to how many samples (per group)?",
value = 500,
min = 5,
max = 999,
step = 1),
shiny::selectizeInput("power_comps", "Which comparisons do you want to make?",
choices = c(" "),
multiple = T),
shiny::numericInput("power_fdr", "False discovery rate:",
value = 0.1,
max = 1,
min = 0.00001),
shinyWidgets::actionBttn(
inputId = "do_power",
label = "click to start power analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_power_plots",
shiny::uiOutput("power_plot_wrap")
)
))
),
shiny::tabPanel("enrichment", value = "enrich",
sidebarLayout(position = "left",
sidebarPanel = sidebarPanel(
shiny::fluidRow(align="center",
h3("Enrichment parameters"),
shiny::selectizeInput("mummi_org",
label = "Pathway KEGG database:",
choices = list(
"Homo sapiens (human)"="hsa01100",
"Sus scrofa (swine)"="ssc01100",
"Microbial metabolism in diverse environments"="map01120",
"Bos taurus (cow)"="bsa01100",
"Mus musculus (mouse)"="mmu01100",
"Rattus norvegicus (rat)"="rno01100",
"Danio rerio (zebrafish)"="dre01100",
"Caenorhabditis elegans (nematode)"="cel01100",
"Gallus gallus (chicken)"="gga01100",
"Escherichia coli K-12 MG1655"="eco01100"
), selected = "hsa01120",options = ),# REGEX: [:|"|,][A-z]+?_[A-z]+?[:|"|,] ON the metaboanalyst page showing the table with options
shinyWidgets::switchInput(
inputId = "mummi_enr_method",value = TRUE,
onLabel = "mummichog",
offLabel = "gsea"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shinyWidgets::switchInput(
inputId = "mummi_rules",
value = FALSE,
onLabel = "yes",
label = "Apply adduct rules?",
offLabel = "no"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::textInput("mummi_pval", label = "Required p-value:", value = "0.005"),
br(),
h3("User data parameters"),
shiny::selectizeInput("mummi_anal",
"Use analysis:",
choices = c("none available"),
selected = 1,
multiple = F),
shiny::sliderInput("mummi_topn",
"Top hits used:",
min = 10,
max = 5000,
step = 1,
value = 100),
shinyWidgets::pickerInput(inputId = "mummi_adducts",
choices = adducts$Name,
label = "Adducts to look for:",
selected = c("[M+H]1+", "[M+Na]1+", "[M+2H]2+", "[M+K]1+"),
multiple = T,
options = list(
`actions-box` = TRUE)),
shiny::uiOutput("mummi_adducts_cats"),
shinyWidgets::actionBttn(
inputId = "do_enrich",
label = "click to start enrichment analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
)),
mainPanel = mainPanel(fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_enrich",multiple=T,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_enrich_plots",
shiny::tabsetPanel(id = "enrich_results",
shiny::tabPanel("overview",
shiny::uiOutput("enrich_plot_wrap"),
shinyWidgets::switchInput("enrich_plot_mode", "Plot type:",
onLabel = "point", offLabel = "bar",
value = T),
shinyWidgets::switchInput("enrich_sig_only","Only color significant hits?",
onLabel = "yes", offLabel = "no",
value = F),
),
shiny::tabPanel("selected pathway",
shinyWidgets::switchInput("enrich_pathway_plot_mode", "Style:",
onLabel="kegg",
offLabel="generic", value=T),
shiny::actionButton("enrich_plot_pathway", "Plot pathway"),
shiny::wellPanel(id = "pathway_panel",
style = "overflow-y:scroll; overflow-x:scroll; max-height: 600px",
imageOutput("enrich_pathway"))
))
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_enrich_tables",
shiny::div(DT::dataTableOutput("enrich_tab",
width="100%"),
style='font-size:80%'),
shiny::div(DT::dataTableOutput("enrich_pw_tab",
width="100%"),
style='font-size:80%'))
)
))
)
),
# PUT IT HERE
shiny::tabPanel("feature selection",
value="featsel",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_featsel",
multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),
value="collapse_featsel_settings",
shinyWidgets::actionBttn(
inputId = "do_featsel",
label = "click to start Boruta feature selection",
style = "bordered",
icon = icon("terminal"),
size = "sm")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_featsel_tables",
shiny::div(DT::dataTableOutput('featsel_tab',
width="100%"),
style='font-size:80%')
)
)
))
),
shiny::tabPanel("machine learning",
value = "ml", icon=shiny::icon("signature", "fa-2x"),
shiny::br(),
shiny::tabsetPanel(id = "ml2",
shiny::tabPanel("configure",icon = icon("cog"),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shiny::tags$h3("Job name"),
shiny::icon("signature", "fa-3x"),
shiny::textInput("ml_name",
label="",
value = stringi::stri_rand_strings(1,
10,
pattern = "[A-Za-z0-9]"))
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width = 3,
shiny::tags$h3("Input data"),
shiny::icon("table", "fa-3x"),
hr(),
shinyBS::bsCollapse(
shinyBS::bsCollapsePanel("Used data",
shiny::selectizeInput("ml_used_table",
label = "Used data:",
choices = list("orig", "prebatch", "norm", "pca"),
selected = "norm"),
shiny::selectizeInput("ml_include_covars",
label = "Use which metadata for prediction?",
choices=c(" "), multiple=TRUE)
),
shinyBS::bsCollapsePanel("Used samples",
shiny::selectizeInput("ml_samp_distr", label = "Reuse train/test sample distribution from previous experiment?",
choices=c(" "), multiple=FALSE),
shiny::conditionalPanel("input.ml_samp_distr == ' '",
shiny::selectInput("ml_tr_te_subset",
"Train or test on a metadata-based subset of the data?",
choices = c("yes","no")),
shiny::conditionalPanel("input.ml_tr_te_subset == 'yes'",
shiny::helpText("Train on subset:"),
shiny::fluidRow(sardine(shiny::textOutput("ml_train_ss")),
shinyWidgets::circleButton(inputId = "reset_ml_train",
icon=shiny::icon("undo"),
size = "xs",
status = "warning"),br(),
shinyWidgets::circleButton("ml_train_ss", label = ":",
icon = shiny::icon("arrow-left"))),
shiny::helpText("Test on subset:"),
shiny::fluidRow(sardine(shiny::textOutput("ml_test_ss")),
shinyWidgets::circleButton(inputId = "reset_ml_test",
icon=shiny::icon("undo"),
size = "xs",
status = "warning"),br(),
shinyWidgets::circleButton("ml_test_ss",
icon = shiny::icon("arrow-left")))
),
shiny::conditionalPanel("input.ml_tr_te_subset == 'no'",
shiny::sliderInput("ml_train_perc",
label = "Percentage of samples in training",
min = 1,
max = 100,
step = 1,
value = 80,
post = "%"))
)
),
shinyBS::bsCollapsePanel("Used m/z",
shiny::selectizeInput("ml_specific_mzs", label = "Analysis-based top hits", choices=c(" "), multiple=FALSE),
shiny::conditionalPanel("input.ml_specific_mzs != 'no'",
shiny::conditionalPanel("input.ml_specific_mzs == 'manual'",
div(shinyWidgets::pickerInput(
inputId = "ml_mzs",
label = div(icon("search"),
style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "fa-cat",
multiple = T,
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker")),
shiny::conditionalPanel("input.ml_specific_mzs != 'manual'",
shiny::sliderInput('ml_mzs_topn',
label = "Use top:",min = 1,max=200,value = 20),
shinyWidgets::switchInput("ml_mzs_rand",
label = "Randomize order?",
value = F,
onLabel = "yes",
offLabel = "no"),
shiny::textOutput("ml_specific_mzs_sigcount")
)
)
)
)
),
shiny::column(width = 1,
shiny::icon("caret-right", "fa-5x vertical-center")
),
shiny::column(width = 3,
shiny::tags$h3("Data adjustment"),
shiny::icon("shower", "fa-3x"),
hr(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Batch correction",
value="ml_batch_panel",
shiny::selectizeInput("ml_batch_covars", label = "Batch metadata column:",
choices=c(" "),
multiple=F),
shiny::helpText("Balance classes per batch factor?"),
shinyWidgets::switchInput(
inputId = "ml_batch_balance",
value = FALSE,
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::helpText("If batch present, make all batches same size in TOTAL? Otherwise each batch will have the right percentage train/test but one batch may be larger than another in TOTAL.:"),
shinyWidgets::switchInput(
inputId = "ml_batch_size_sampling",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = FALSE
),
shiny::conditionalPanel("input.ml_batch_size_sampling == true",
shiny::numericInput("ml_groupsize",
label = "Size per experimental group (auto: 0):",
value = 0)))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Class balancing",
shinyWidgets::radioGroupButtons(
inputId = "ml_sampling",
label = "How to balance class labels?:",
choices = c(`<i class='fa fa-arrow-down'></i> downsample` = "down",
`ROSE` = "rose",
`SMOTE` = "smote",
`ADASYN` = "adasyn",
`don't` = "none",
`upsample <i class='fa fa-arrow-up'></i>` = "up"),
justified = FALSE,
selected = "none"
)
)),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Miscellanaous",
shiny::selectizeInput("ml_preproc", label = "Data preprocessing",
choices = c("center", "scale"),
selected = c(), multiple=T),
shinyWidgets::switchInput(
inputId = "ml_pca_corr",
value = FALSE,
label = "PCA correction",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::conditionalPanel("input.ml_pca_corr == true",
sliderInput("ml_keep_pcs",
label = "Keep variance in PCs:",
min = 0,
max = 300, value = c(10, 50))
)
))
),
shiny::column(width = 1,
shiny::icon("caret-right", "fa-5x vertical-center")
),
shiny::column(width = 3,
shiny::tags$h3("Model settings"),
shiny::icon("sliders-h", "fa-3x"),
hr(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Algorithm",
shiny::selectizeInput("ml_method",
label = "Used algorithm",
selected = "glmnet",
choices = as.list(gbl$constants$ml.models),
multiple = F),
shiny::div(shiny::uiOutput("ml_params"), style = "font-size:60%"))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title = "Cross validation",
shiny::selectizeInput("ml_perf_metr",
label="Performance metric",
choices = c("boot", "boot632", "optimism_boot",
"boot_all", "cv", "repeatedcv",
"LOOCV", "LGOCV", "none", "oob",
"timeslice", "adaptive_cv",
"adaptive_boot","adaptive_LGOCV"),
multiple = F, selected = "cv"),
shiny::selectizeInput("ml_folds", label="Fold CV",choices = c("5",
"10",
"20",
"50",
"LOOCV"),
multiple = F))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Significance",
shiny::helpText("Calculate p-value using shuffled labels?"),
shinyWidgets::switchInput(
inputId = "ml_label_shuffle",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = FALSE
),
shiny::conditionalPanel("input.ml_label_shuffle == true",
shiny::numericInput("ml_n_shufflings",
"Number of randomized models:",
value=1, min=1, max=NA),
shiny::helpText("Shuffle train or testing labels?"),
shinyWidgets::switchInput(
inputId = "ml_shuffle_mode",
value = TRUE,
onLabel = "train",
offLabel = "test",
size = "small")
)))
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shinyWidgets::actionBttn(
inputId = "queue_ml",
label = "add to queue",
style = "bordered",
icon = icon("plus"),
size = "sm"
),
shinyWidgets::actionBttn(
inputId = "queue_ml_del",
label = "remove from queue",
style = "bordered",
icon = icon("minus"),
size = "sm"
))
),
br(),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shinyWidgets::actionBttn(
inputId = "do_ml",
label = "start ML queue",
style = "bordered",
icon = icon("terminal"),
size = "l"
)
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width=6,
shiny::tags$h3("Job queue"),
shiny::icon("list-ol", "fa-3x"),
br(),br(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Advanced",
value="ml_queue_panel",
shiny::textInput("queue_ml_name",
label = "Queue (file) name:",
value = "my_queue"),
shinyWidgets::actionBttn(
inputId = "queue_ml_save",
label = "save queue",
style = "bordered",
icon = icon("terminal"),
size = "sm"
),
shiny::fileInput(
inputId = "queue_ml_load",
label = "load queue"
))),
DT::DTOutput("ml_queue_all")),
shiny::column(width=5,
shiny::tags$h3("Job settings"),
shiny::icon("cogs","fa-3x"),
shiny::br(), shiny::br(),
DT::DTOutput("ml_queue_sel"))
)
),
shiny::tabPanel("results", value="res",icon = icon("chart-area"),
shiny::fluidRow(align="center",
shiny::selectizeInput("show_which_ml",
label = "Plot which model?",
choices = c(" ")),
shiny::actionButton("clear_ml_runs", "clear results", icon=icon("broom"))),
shiny::tabsetPanel(id="ml_results",
shiny::tabPanel(title = "curves",value = "roc",icon=shiny::icon("area-chart"),
shiny::fluidRow(align="center",shiny::uiOutput("ml_roc_wrap")),
shiny::fluidRow(align="center",
shiny::column(4,
shiny::selectizeInput("ml_plot_posclass",
label = "Positive class",
choices = c("placeholder"),
selected=c("placeholder")
)
),
shiny::column(3,
shiny::selectizeInput("ml_plot_x",
"Metric for x axis:",
choices = list("Accuracy"="acc",
"Error rate"="err",
"False positive rate"="fpr",
"True positive rate"="tpr",
"Fallout"="fall",
"Recall"="rec",
"Sensitivity"="sens",
"False negative rate"="fnr",
"Miss"="miss",
"True negative rate"="tnr",
"Positive predictive value"="ppv",
"Precision"="prec",
"Negative predictive value"="npv",
"Precision-conditioned fallout"="pcfall",
"Precision-conditioned miss"="pcmiss",
"Rate of positive predictions"="rpp",
"Rate of negative predictions"="rnp",
"Phi correlation coefficient"="phi",
"Matthews' corelation coefficient"="mat",
"Mutual information"="mi",
"Chi square test statistic"="chisq",
"Odds ratio"="odds",
"Lift value"="lift",
"Precision-recall F value"="f",
"Cutoff"="cutoff"),
selected = "fpr")),
shiny::column(3,
shiny::selectizeInput("ml_plot_y",
"Metric for y axis:",
choices = list("Accuracy"="acc",
"Error rate"="err",
"False positive rate"="fpr",
"True positive rate"="tpr",
"Fallout"="fall",
"Recall"="rec",
"Sensitivity"="sens",
"False negative rate"="fnr",
"Miss"="miss",
"True negative rate"="tnr",
"Positive predictive value"="ppv",
"Precision"="prec",
"Negative predictive value"="npv",
"Precision-conditioned fallout"="pcfall",
"Precision-conditioned miss"="pcmiss",
"Rate of positive predictions"="rpp",
"Rate of negative predictions"="rnp",
"Phi correlation coefficient"="phi",
"Matthews' corelation coefficient"="mat",
"Mutual information"="mi",
"Chi square test statistic"="chisq",
"Odds ratio"="odds",
"Lift value"="lift",
"Precision-recall F value"="f",
"Cutoff"="cutoff"),
selected = "tpr")),
column(2, actionButton(inputId = "reload_ml_stats", "Go"))),
fluidRow(
shiny::column(6, shiny::div(DT::dataTableOutput("ml_overview_tab",
width="100%"),
style='font-size:80%')),
shiny::column(6, shiny::plotOutput("conf_matr_plot"))
)
),
# shiny::tabPanel("mistakes & metadata",value="bar",icon=shiny::icon("times"),
# shiny::fluidRow(align="center",shiny::uiOutput("ml_mistake_wrap"),
# shiny::selectizeInput("ml_mistake_var",
# label = "Check percentage mistaken for which metadata column?",
# choices = "",
# multiple = F),
# shinyWidgets::switchInput(
# inputId = "ml_mistake_smooth",
# size = "small",
# onLabel = "smoothed",
# offLabel = "raw",
# value = F
# ),
# shinyWidgets::switchInput(
# inputId = "ml_mistake_per_rep",
# size = "small",
# onLabel = "per repeat",
# offLabel = "average repeats",
# value = FALSE
# ),
# shinyWidgets::actionBttn(
# inputId = "plot_ml_mistake",
# label = "click to plot",
# style = "bordered",
# icon = icon("pencil-alt"),
# size = "sm"
# ))
# ),
shiny::tabPanel("importance",value="bar",icon=shiny::icon("star"),
shiny::fluidRow(align="center",
shiny::uiOutput("ml_bar_wrap"),
shiny::sliderInput("ml_topn",
label = "Show top:",
min = 10,
max = 200,
step=10,
value=20),
shiny::div(DT::dataTableOutput("ml_importance_tab",
width="100%"),
style='font-size:80%')
)
),
shiny::tabPanel("used settings", value="param", icon=shiny::icon("cog"),
shiny::div(DT::dataTableOutput("ml_param_tab",
width="50%"))
)
)
))
))
),
# this is the sidebar that shows in the analysis tab. contains a lot of settings on the current variable of interest, plot themes and colours, and venn diagrams.
sidebarPanel =
shinyjqui::jqui_resizable(
sidebarPanel(align="center",width = 3,id="sidePanel",
shiny::fluidRow(align="center",
shiny::tabsetPanel(id = "anal_sidebar", selected="start",
shiny::tabPanel(title=shiny::icon("star"),value = "start",
shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),
tags$i("Load a dataset to get started!"),
br(),
icon("caret-down", "fa-3x"),
br(),
icon("box-open","fa-5x"),
shiny::br(),shiny::br(),shiny::br(),
shiny::br(),shiny::br()),
shiny::tabPanel(value="switch",
title=shinyBS::tipify(shiny::icon("exchange"),
title = "switch to different variable and/or subset based on variable",
trigger = "hover",options=list(container="body"))
, shiny::h2("Current experiment:"),
shiny::div(
shiny::div(style="display: inline-block;vertical-align:top;",shiny::uiOutput("curr_name")),
style="background-color:white;
width:100%;
margin: 0 auto;
border-top: 1px solid #DFDCDC;
border-bottom: 1px solid #DFDCDC;")
,shiny::hr()
,shiny::h2("Change variable of interest")
,shiny::selectizeInput("stats_type",
label = "Normal, two-factor or time series?",
choices = list("one factor" = "1f",
"two factors" = "2f",
"time series" = "t",
"time series + one factor" = "t1f"),
selected = "1f",width = "80%")
,fluidRow(align="center",shiny::uiOutput("stats_picker"))
,shiny::conditionalPanel("input.stats_type == '1f'",
shiny::checkboxInput("paired",
"Matched samples only?",
value = F))
,shiny::conditionalPanel("input.stats_type == 't' || input.stats_type == 't1f'",
shiny::selectizeInput("time_var",
label="Time series variable:",
choices = c(" "),width = "80%"))
,shinyWidgets::actionBttn(
inputId = "change_cls",
label = "do stats on selected",
style = "bordered",
icon = icon("magic"),
size = "sm"
)
),
shiny::tabPanel(value="subset",
title=shinyBS::tipify(shiny::icon("filter"),
title = "Subset based on variable or m/z(s)",
trigger = "hover",options=list(container="body")),
shiny::hr()
,shiny::h2("Subset data")
,helpText("Current sample count:")
,h2(shiny::textOutput("samp_count"))
,helpText("Current m/z count:")
,h2(shiny::textOutput("mz_count"))
,br()
,shiny::selectizeInput("subset_var", label="Subset data based on:", choices = c(" "),width = "80%")
,shinyWidgets::pickerInput(
inputId = "subset_group",
label = "Group(s) in subset:",
choices = c(" "),
choicesOpt = list(
subtext = c(" ")
),multiple = T)
,shinyWidgets::actionBttn(
inputId = "change_subset",
label = "click to subset by metadata",
style = "bordered",
icon = icon("filter"),
size = "sm"
),br(),br()
# ,shinyWidgets::pickerInput(
# inputId = "subset_mzs",
# label = "Subset by m/z(s):",
# choices = c("M/z with prematches"="prematched"),
# choicesOpt = list(
# subtext = c(" ")
# )),
# shiny::conditionalPanel("input.subset_mzs == 'prematched'",
# shiny::helpText("Only use matches with main isotopes??"),
# shinyWidgets::switchInput(
# inputId = "subset_mz_iso",
# size = "mini",
# onLabel = "Yes",
# offLabel = "No",
# value = TRUE
# )
# ),
# shinyWidgets::actionBttn(
# inputId = "change_subset_mz",
# label = "click to subset by m/z",
# style = "bordered",
# icon = icon("filter"),
# size = "sm"
# ),
# br(),br()
,shinyWidgets::pickerInput(
inputId = "storage_choice",
label = "Load existing meta-dataset:",
choices = c(" "),
choicesOpt = list(
subtext = c(" ")
))
,span(shinyWidgets::actionBttn(
inputId = "load_storage",
label = "load",
style = "bordered",
icon = icon("folder-open"),
size = "sm",
color = "success"
),
shinyWidgets::actionBttn(
inputId = "remove_storage",
label = "delete",
style = "bordered",
icon = icon("eraser"),
size = "sm",
color = "warning"
))
,br(),br()
,helpText("Reset to non-subsetted or paired dataset")
,shinyWidgets::actionBttn(
inputId = "reset_subset",
label = "click to un-subset data",
style = "bordered",
icon = icon("undo"),
size = "sm"
)
),
shiny::tabPanel(value="search",title=shinyBS::tipify(shiny::icon("search"),
title = "search m/z > compound or compound > mz",
trigger = "hover",options=list(container="body")),
shiny::br(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Options"),
value="search_panel",
shiny::tabsetPanel(id="tab_iden_1", selected = "pick_databases",
# forward searching
shiny::tabPanel(title = shiny::icon("database"),
#title="DBs",
value = "pick_databases",
shiny::uiOutput("db_search_select"),
br(),
shiny::div(id = "curly-brace", shiny::div(id = "left", class = "brace"),
shiny::div(id = "right", class = "brace")),
br(),br(),
shinyWidgets::circleButton("select_db_all",
icon = shiny::icon("shopping-cart"),
size = "default") # shiny::icon("fingerprint"), size = "sm")
),
shiny::tabPanel(title = icon("medal"),
shiny::fluidRow(
shiny::helpText("Only consider highly correlated m/z values?"),
shinyWidgets::switchInput(
inputId = "score_use_corr",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::conditionalPanel("input.score_use_corr == true",
shiny::selectizeInput(width = "80%","score_corr_method",
"Which correlation method used?",
selected="pearson",
choices=list("pearson",
"spearman",
"kendall"
)),
shiny::sliderInput("score_corr_min",
label = "Min required correlation: ",
min = 0, max = 1,
value = 0.9,
step = 0.05)
)
),
shiny::tabsetPanel(
shiny::tabPanel(title=icon("percentage"),#title="isoScore",
shiny::fluidRow(align="center",
shiny::br(),
shiny::h2("isoMatcher"),
shiny::h3("Score matches by isotope pattern"),
shiny::helpText("Per match, investigates if other same-formula isotopes are present."),
shiny::helpText("Score pattern intensity simularity? (if not, only check for isotope presence)"),
shinyWidgets::switchInput(
inputId = "iso_use_int",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::conditionalPanel("input.iso_use_int == true",
shiny::selectizeInput(width = "80%","iso_score_method",
"Which method used to score compounds of same weight?",
selected="mscore",
choices=list("M-score" = "mscore"
#"Chi-square" = "chisq",
#"Mean absolute percentage error" = "mape",
#"SIRIUS" = "sirius",
#"Network-based" = "network"
)),
shiny::sliderInput("int_prec",
label = "Intensity error margin",
min = 1, max = 100,
value = 2, post = "%")
),
shiny::uiOutput("iso_rt_ui"),
shinyWidgets::circleButton("score_iso", icon = shiny::icon("medal"), size = "sm"))
),
shiny::tabPanel(title=shiny::icon("clock"),
shiny::fluidRow(align="center",
shiny::br(),
shiny::h2("addMatcher"),
shiny::h3("Score matches by fellow adducts"),
shiny::helpText("Per match, investigates if other main isotope adducts are present."),
shinyWidgets::pickerInput(inputId = "score_adducts",
choices = adducts$Name,
label = "Adducts to look for:",
selected = c("[M+H]1+", "[M+Na]1+", "[M+2H]2+", "[M+K]1+"),
multiple = T,
options = list(
`actions-box` = TRUE)),
shiny::uiOutput("score_adducts_cats"),
shiny::uiOutput("add_rt_ui"),
shinyWidgets::circleButton("score_add",
icon = shiny::icon("medal"),
size = "sm")
))
)
),
shiny::tabPanel(title=shiny::icon("cloud"),#title="wordcloud",
tabsetPanel(id="wordclouds", selected = "settings",
tabPanel(title="settings",
shiny::br(),
shinyWidgets::switchInput(
inputId = "wordcloud_manual",value = TRUE,
onLabel = "own word",#<i class=\"fas fa-cloud\"></i>",
offLabel = "from matches"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::tabPanel("input.wordcloud_manual == true",
helpText("Type a metabolite below and search PubMed to find documents that contain that word in the text."),
textInput("wordcloud_searchTerm", label = h3("Enter your search terms"), placeholder = "enter your search terms"),
helpText("You can specify the start and end years of your search, use the format YYYY"),
sliderInput(inputId = "wordcloud_dateRange", label = "Date range input:",min = 2000, max = 2025, value = c(2010, 2020), sep = ""),
sliderInput("wordcloud_absFreq", "Amount of abstracts to use:", min = 1, max = 4000, value = 500)
),
actionButton("do_wordcloud", "Plot")
),
tabPanel(title = "filters",
helpText("Type a search term: a word filter will be created with the resulting top words."),
textInput("wordcloud_filterTerm", label = h3("Enter your search terms"), placeholder = "enter your search terms"),
helpText("You can specify the start and end years of your search, use the format YYYY"),
sliderInput(inputId = "wordcloud_filterDateRange", label = "Date range input:",min = 2000, max = 2025,value = c(2010, 2020), sep = ""),
sliderInput("wordcloud_filterAbsFreq", "Amount of abstracts to use:", min = 10, max = 500000, value = 5000),
sliderInput("wordcloud_filterTopN", "Top words used for filter:", min = 1, max = 5000, value = 500),
actionButton("wordcloud_make_filter", "Go! :)")
),
tabPanel(title = "plot",
shiny::conditionalPanel('input.wordbar == true',
wordcloud2::wordcloud2Output(outputId = "wordcloud"),
tags$script(HTML(
"$(document).on('click', '#canvas', function() {",
'word = document.getElementById("wcSpan").innerHTML;',
"Shiny.onInputChange('wordcloud_selected_word', word);",
"});"
))
),
conditionalPanel('input.wordbar == false',
shiny::uiOutput("wordbar_wrap")
),
shinyWidgets::switchInput(
inputId = "wordbar",value = TRUE,
onLabel = "cloud",#<i class=\"fas fa-cloud\"></i>",
offLabel = "barchart"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
br(),
shiny::sliderInput("wordcloud_topWords", "Top words used for plot:", min = 1, max = 10000, value = 100),
shiny::selectizeInput("wordcloud_filter",
"Filter",
choices = c("stopwords"),
selected="stopwords",
multiple = T),
shiny::wellPanel(id = "def",style = "overflow-y:scroll; max-height: 400px; font-size: 80%",
helpText("Click a word to see abstracts!"),
shiny::uiOutput("wordcloud_abstracts")
)
)
)
)
))),
br(),
shiny::uiOutput("manual_search"),
br(),
div(shiny::fluidRow(align="center",
div(
br(),br(),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shinyWidgets::pickerInput(
inputId = "curr_mz",
label = div(icon("search"), style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "fa-cat",
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
br(),
style = "align-items: center; display: inline-flex;"),
),
shinyWidgets::prettyToggle(
status_off = "default",
status_on = "warning",
bigger = T,
animation = "pulse",
inputId = "star_mz",
label_on = "",
label_off = "",
outline = TRUE,
plain = TRUE,
value = FALSE,
icon_on = icon("star"),
icon_off = htmltools::browsable(tags$i(class = "far fa-star"))
),
style = "border-top: 1px solid #DFDCDC; border-bottom: 1px solid #DFDCDC; margin-left: -15px; margin-right: -15px; background-color:white;"),
br(),
shiny::tabsetPanel(id = "tab_search", shiny::tabPanel(title = shinyBS::tipify(shiny::icon("paw"),
"mz <> molecule matches"),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Compound info"),
value="panel2",
shiny::tabsetPanel(id="tab_iden_3",
shiny::tabPanel(title=shiny::icon("atlas"),
wellPanel(id = "def",style = "overflow-y:scroll; max-height: 200px",
shiny::uiOutput("desc_ui")
)
),shiny::tabPanel(title=shiny::icon("atom"),
br(),
shiny::imageOutput("empty4",width="100%",height="1px"),
shiny::uiOutput("curr_formula"),
shiny::plotOutput("curr_struct",inline = T)
)
))),
shiny::tabsetPanel(id="tab_iden_2",
# forward searching
shiny::tabPanel(title="mz > molecule",value = "mzmol",
br(),
shiny::tags$i("Found matches for this m/z value:"),
br(),
shinyWidgets::searchInput(
inputId = "match_search_query",
label = "Search compound descriptions",
placeholder = "",
btnSearch = icon("search"),
btnReset = icon("remove"),
width = "100%"
),
shiny::fluidRow(align="left",
shiny::div(DT::dataTableOutput('match_tab'),
style='font-size:80%;'))
),
# reverse searching
shiny::tabPanel(title="molecule > mz",value = "molmz",
br(),
shiny::tags$i("Press the below button to browse compounds of the selected databases."),br(),
shiny::actionButton("browse_db", "Browse", icon=shiny::icon("eye")),
br(),
shiny::div(DT::dataTableOutput('browse_tab'),style='font-size:80%'),
br(),
shiny::tags$i("M/z values matching adducts or isotopes of this compound:"),br(),
shiny::div(DT::dataTableOutput('hits_tab'),style='font-size:80%')
)),
shiny::fluidRow(
shiny::div(shiny::helpText("Show heavy C, N, O count if available?"),
style='font-size:80%;'),
shinyWidgets::switchInput(
inputId = "show_iso_labels",
size = "mini",
onLabel = "show",
offLabel = "hide",
value = FALSE
)),
br(),
shiny::helpText("Current match filtering:"),
shiny::fluidRow(align="center",
shiny::imageOutput("empty",width="100%",height="1px"),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("plus-circle")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_add"),style='font-size:60%;padding:2px')),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("percentage")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_iso"),style='font-size:60%;padding:2px')),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("database")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_db"),style='font-size:60%;padding:2px'))
),
shiny::helpText("Undo match filtering"),
shinyWidgets::circleButton("undo_match_filt", icon = shiny::icon("undo-alt")),
br()
),
shiny::tabPanel(title=shinyBS::tipify(shiny::icon("filter"),
title = "filter matches on adduct, isotope or database"),
value="match_filters_tab",
shinyWidgets::verticalTabsetPanel(id = "match_filters",
contentWidth = 10,
menuSide = "right",
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("plus","fa-2x"),value = "pie_add",
plotly::plotlyOutput("match_pie_add"),
shiny::uiOutput("filter_adducts_cats")
),
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("percentage","fa-2x"),value = "pie_iso",
plotly::plotlyOutput("match_pie_iso")
),
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("database","fa-2x"),value = "pie_db",
plotly::plotlyOutput("match_pie_db")
)
),br()
))),
# this tab is used to select user plot theme and user colours (discrete and continuous)
shiny::tabPanel(value="plot_aes", title=shinyBS::tipify(shiny::icon("paint-brush"),
title="change plot style and colours",
trigger = "hover",options=list(container="body")),
shiny::h2("Plot style"),br(),
helpText("Click to reload plot:"),
shinyWidgets::circleButton("reload_plots",
icon = shiny::icon("paint-brush")),
br(),
helpText("Use ggplot or plotly for plots? (ggplot -> faster, but no interactivity)"),
shinyWidgets::switchInput(
inputId = "ggplotly",
onLabel = "plotly",
offLabel = "ggplot",
offStatus = "warning",
onStatus = "info",
value = T
),
helpText("Export plots as .png or .svg?"),
shinyWidgets::switchInput(
inputId = "plotsvg",
onLabel = "svg",
offLabel = "png",
offStatus = "info",
onStatus = "warning",
value = T
),
shiny::h2("Legend"),br(),
shinyWidgets::switchInput(
inputId = "legend",
size = "mini",
onLabel = "show",
offLabel = "hide",
value = FALSE
),
shiny::h2("M/z labels"),
shiny::tags$i("only ggplot mode"),
shinyWidgets::switchInput("plot_mzlabels", value = T, onLabel = "show", offLabel="hide", size = "small"),
shiny::numericInput("ggplot_font_size",label = "Plot font base size:",value = 15),
plotly::plotlyOutput("ggplot_font_size_example"),
shiny::selectizeInput("ggplot_sum_style", multiple=T, label = "Style(s)", choices = list("Box" = "box",
"Violin" = "violin",
"Beeswarm" = "beeswarm",
"Scatterplot" = "scatter",
"Sina" = "sina"
),
selected = c("beeswarm"),width = "80%"),
shiny::selectizeInput("ggplot_sum_stats", label = "Stats shown", choices = list("median", "mean", "none"),width = "80%"),
shiny::h2("Shape")
,shiny::selectizeInput("shape_var", label="Marker shape based on:", choices = c(" "),width = "80%")
,shiny::h2("Color")
,shiny::selectizeInput("fill_var", label="Marker fill color based on:", choices = c(" "),width = "80%")
,shiny::selectizeInput("col_var", label="Marker outline color based on:", choices = c(" "),width = "80%")
,shiny::h2("Hover text")
,shiny::selectizeInput("txt_var", label="Marker hover text based on:", choices = c(" "),width = "80%"),
# input$plot_mzlabels
shiny::h2("Plot theme"),
shiny::selectizeInput("ggplot_theme", label = "Theme", choices = list("Grid, white bg" = "bw",
"No grid, white bg" = "classic",
"Grid, gray bg" = "gray",
"Minimal" = "min",
"Grid, black bg" = "dark",
"Grid, white bg, gray axes" = "light",
"Line drawing" = "line"),
selected = "min",width = "80%"),
plotly::plotlyOutput("ggplot_theme_example",inline = F),
shiny::h2("Continuous data"),
# the below options need to match with the corresponding function storage in 'global'. if you want to add more it'll go here!
shiny::selectizeInput("color_ramp", label = "Color scheme", choices = list("RAINBOW!" = "rb",
"Yellow - blue" = "y2b",
"Matlab 1" = "ml1",
"Matlab 2 " = "ml2",
"Magenta - Green" = "m2g",
"Cyan - yellow" = "c2y",
"Blue - yellow" = "b2y",
"Green - red" = "g2r",
"Blue - green" = "b2g",
"Blue - red" = "b2r",
"Blue - pink (pastel)" = "b2p",
"Blue - green - yellow" = "bgy",
"Green - yellow - white" = "gyw",
"Red - yellow - white" = "ryw",
"Grayscale" = "bw",
"Blues (brew)" = "Blues",
"Blue - green (brew)" = "BuGn",
"Blue - purple (brew)" = "BuPu",
"Green - blue (brew)" = "GnBu",
"Greens (brew)" = "Greens",
"Grayscale (brew)" = "Greys",
"Oranges (brew)" = "Oranges",
"Orange - red (brew)" = "OrRd",
"Purple - blue (brew)" = "PuBu",
"Purple - blue - green (brew)" = "PuBuGn",
"Purple - red (brew)" = "PuRd",
"Purples (brew)" = "Purples",
"Red - purple (brew)" = "RdPu",
"Reds (brew)" = "Reds",
"Yellow - green (brew)" = "YlGn",
"Yellow - green - blue (brew)" = "YlGnBu",
"Yellow - orange - brown (brew)" = "YlOrBr",
"Yellow - orange - red (brew)" = "YlOrRd",
"BrBG", "PiYG", "PRGn", "PuOr", "RdBu", #TODO: add descriptions (or remove all?)
"RdGy", "RdYlBu", "RdYlGn", "Spectral",
"Accent", "Dark2", "Paired", "Pastel1",
"Pastel2", "Set1", "Set2", "Set3"),selected = "rainbow",width = "80%"
),
# preview plot
plotly::plotlyOutput("ramp_plot"),
shiny::h2("Discrete data"),
shiny::uiOutput("colorPickers")
),
shiny::tabPanel(value="metadata",
title = shinyBS::tipify(shiny::icon("plus"),
trigger = "hover",
title = "upload new metadata file",options=list(container="body")),
br(),br(),
shiny::h2("New metadata"),
shiny::helpText("If you want to update your metadata, please use the below upload screen!
Any samples missing in your uploaded csv will be labeled as 'unknown' for new metadata columns."),
shiny::fileInput(inputId = "metadata_new", "Select metadata", buttonLabel="Browse"),
#shinyFiles::shinyFilesButton('metadata_new', 'upload', 'Select metadata', FALSE),
shinyWidgets::circleButton("metadata_new_add", icon = shiny::icon("arrow-right"))
)))))
))),
# # report tab
# shiny::tabPanel("report",
# icon = shiny::icon("file-invoice", class = "outlined"),
# value="report",
# shiny::fluidRow(align="center", shiny::h2("Report")),
# shiny::fluidRow(
# shiny::column(width=5, align="center",
# shiny::div(DT::dataTableOutput('report_unselected',
# width="100%"))
# ),
# shiny::column(width = 2, align="center",
# shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),
# shinyWidgets::circleButton("report_add", icon=shiny::icon("arrow-right")),
# shiny::br(),
# shinyWidgets::circleButton("report_remove", icon=shiny::icon("arrow-left"))
# ),
# shiny::column(width=5, align="center",
# shiny::div(DT::dataTableOutput('report_selected',
# width="100%"))
# )
# ),shiny::br(),
# shiny::fluidRow(align="center",
# shinyWidgets::circleButton("make_report",
# icon=shiny::icon("file-invoice"),
# size="lg")
# )
# ),
# this tab is used to change general settings.
shiny::tabPanel("settings", icon = shiny::icon("cog",class = "outlined"), value="options",
shiny::tabsetPanel(id="tab_settings",selected = "Global",
shiny::tabPanel("Global", icon=shiny::icon("box-open"),
# MetaboShiny::switchButton(inputId = "db_only", label = "Run in database-only mode?",
# value = F,
# col = "BW", type = "YN")
shiny::fluidRow(align="center",
# work folder
shinyFiles::shinyDirButton("get_work_dir",label = "Change projects folder",title = "Pick projects directory"),
shiny::textOutput("curr_exp_dir"),
# db folder
shinyFiles::shinyDirButton("get_db_dir",label = "Change database folder", title = "Pick database directory"),
shiny::textOutput("curr_db_dir"),br(),
shiny::sliderInput("ncores", "How many cores can MetShi use?",
value = 1, min = 1,
max = 2,step = 1,post = " cores"),
shiny::uiOutput("ncore_ui"),
shiny::br(),
shiny::numericInput("seed", "Which seed do you want to use for randomization?",value = 1337),
shiny::actionButton("set_seed",label = "apply"),
shiny::br(),
shiny::helpText("How to handle samples with missing metadata? (re-checked each subset/switch step)?"),
shinyWidgets::switchInput(
inputId = "omit_unknown",
onLabel = "omit",
offLabel = "keep",
offStatus = "success",
onStatus = "danger",
value = T
),
shiny::br(),
shiny::selectizeInput("beep",
label = "Noise to make after task is done:",
choices = list(
"none",
"ping",
"coin",
"fanfare",
"complete",
"treasure",
"ready",
"shotgun",
"mario",
"wilhelm",
"facebook",
"sword"
), selected = 1)
)
),
shiny::tabPanel("Project", icon=shiny::icon("gift"),
#shiny::textInput(inputId="proj_name", label="Project name", value = ''),
shiny::fluidRow(align="center",
shiny::selectizeInput(inputId="proj_name",
label="Project name",
choices=c("..."), # existing projects in user folder (generated in 'global')
selected = "...",
options=list(create = TRUE)), # let users add new names
shiny::actionButton("set_proj_name", label="Apply"),
shiny::hr(),
shiny::helpText("Clone project (to skip file input w/ different normalization)"),
shiny::textInput(inputId = "proj_clone_name", label = "Cloned project name:"),
shiny::actionButton("clone_proj", label = "Clone")
)
),
shiny::tabPanel("Search", icon = shiny::icon("paw"),
br(),
shiny::fluidRow(align="center",
shinyWidgets::materialSwitch(
inputId = "autocopy",
label = "Copy compound info to clipboard?",
value = TRUE,
status = "success"
),
shiny::conditionalPanel("input.autocopy == true",
shinyWidgets::radioGroupButtons(
inputId = "matchAutocopy",
label = "What info will you copy?",
choices = c("SMILES",
"name",
"formula"),
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"))
)
))),
# change list of adducts used, or add your own
# TODO: fix, i think this is currently non-functional
shiny::tabPanel("Adducts", icon=shiny::icon("plus-square"),
shiny::tabsetPanel(
shiny::tabPanel("Current adducts",
shiny::tabsetPanel(
shiny::tabPanel("Definitions",
shiny::fluidRow(align="center",shiny::h3("Current adduct table:")),
rhandsontable::rHandsontableOutput("adduct_tab",
width='100%',
height='70%'),
shiny::fluidRow(align="center",shiny::fileInput(inputId = "add_tab",
"Import adduct table",
multiple = F,
accept = c(".RData", ".csv")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::actionButton("import_adducts", "Import definitions"))
)
),
shiny::tabPanel("Rules",
shiny::fluidRow(align="center", shiny::h3("Current adduct rules:")),
rhandsontable::rHandsontableOutput("adduct_rules_tab",
width='100%',
height='70%'),
shiny::fileInput(inputId = "add_rule_tab",
"Import adduct rule table",
multiple = F,
accept = c(".RData", ".csv")),
shiny::fluidRow(align="center",
shiny::div(style="display: inline-block;vertical-align:top;",shiny::actionButton("import_adduct_rules", "Import rules"))
)
)
),
shiny::fluidRow(align="center",
shiny::actionButton("save_adducts","Save changes"),
shiny::hr()
)
)
)
),
shiny::tabPanel("Formula prediction & lookup",
icon=shiny::icon("searchengin"),
shiny::fluidRow(align="center",
br(),
shiny::passwordInput("apikey",
label = "If you want to use ChemSpider, please register on their website and enter your API key below.",
value = ""),
shiny::div(style="display: inline-block;vertical-align:top;",shinyWidgets::circleButton("set_api", icon = icon("save"))),shiny::div(style="display: inline-block;vertical-align:top;",shiny::textOutput("api_set")),
selectizeInput("predict_rules",
label = "Use which chemical formula rules?",
choices = c("senior", "lewis", "hc", "chnops", "nops"),
multiple = T,
selected = c()),
selectizeInput("predict_elements", label = "Consider which atoms? (including adducts!)",
choices = c("C","H","N","O","P","S"), selected = c("C","H","N","O","P","S"), multiple = T),
MetaboShiny::switchButton(inputId = "predict_details",
label = "Get detailed PubChem matches? (SLOW, be warned!)",
col = "BW", type = "YN", value = F),
MetaboShiny::switchButton(inputId = "predict_structure_check",
label = "Uniformize ChemSpider/PubChem found structures?",
col = "BW", type = "YN", value = T),
MetaboShiny::switchButton(inputId = "predict_adduct_rules",
label = "Filter ChemSpider/PubChem hits with available structures using your adduct rules?",
col = "BW", type = "YN", value = F))),
# change toolbar colour, text font and size
shiny::tabPanel("Aesthetic", icon=shiny::icon("child"),
shiny::fluidRow(align="center",
shiny::h3("Change app settings"),
shiny::hr(),
shiny::h2("Navigation bar colours"),
colourpicker::colourInput(inputId = "bar.col.1",
label = paste("Inactive background"),
#value = opts$col1,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.2",
label = paste("Active background"),
#value = opts$col2,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.3",
label = paste("Inactive tab text"),
#value = opts$col3,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.4",
label = paste("Active tab text"),
#value = opts$col4,
allowTransparent = FALSE),
shiny::br(),
shiny::a(shiny::h2("Fonts (Google fonts)"), href = "https://fonts.google.com/", target="_blank"),
shiny::textInput(inputId="font.1", label="h1", value = "Leckerli One"),
shiny::textInput(inputId="font.2", label="h2", value = "Leckerli One"),
shiny::textInput(inputId="font.3", label="h3", value = "Open Sans"),
shiny::textInput(inputId="font.4", label="body", value = "Open Sans"),
shiny::br(), # TODO: font size modifier slider
shiny::h2("Font size"),
shiny::sliderInput("size.1", label="h1", value=30,min = 5, max=50),
shiny::sliderInput("size.2", label="h2", value=20,min = 5, max=50),
shiny::sliderInput("size.3", label="h3", value=13,min = 5, max=50),
shiny::sliderInput("size.4", label="body", value=10,min = 5, max=50),
shiny::hr(),
shiny::actionButton("change_css", "Save settings (restart to apply)")
)
)
)
),
shiny::tabPanel("help", icon=shiny::icon("question",class="outlined"),
shiny::fluidRow(align = "center",style="li { display:inline-table; }",
shiny::uiOutput("help"))),
# prompt user on opening the quit tab.
# TODO: add 'save project?' dialog
shiny::div(class="scallop-down"),
shiny::div(class="cursorHolder"),
shiny::div(class="line"),
footer=
shiny::div(class = "footer",
shiny::fluidRow(align="center",
shiny::span(shiny::tags$i(icon("map-marker"),
shiny::textOutput("proj_name",inline = T),
style="vertical-align: middle;")),
shiny::actionButton("load_mset", label="load",
icon = shiny::icon("folder-open")),
shiny::actionButton("save_mset", label="save",
icon = shiny::icon("save")),
shiny::actionButton("debug_metshi", label="send to R",
icon = shiny::icon("r-project")),
shiny::actionButton("quit_metshi", label="quit", icon = shiny::icon("eraser")),
shiny::span(shiny::tags$i(icon("stopwatch"), shiny::textOutput("last_saved",inline = T), style="vertical-align: middle;")),
shiny::span(shiny::uiOutput("has_unsaved_changes",inline = T), style="margin-left: 10px;")
)
)
), style="margin-bottom:100px;")
)
UMCUGenetics/MetaboShiny documentation built on Sept. 30, 2021, 11:46 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
shiny::fluidPage(theme = "metaboshiny.css",
class="hidden",id="metshi",
ECharts2Shiny::loadEChartsLibrary(),
shinyalert::useShinyalert(),
shinyjs::useShinyjs(),
tags$head(tags$script(src="cursor.js")),
shiny::div(style = 'position: absolute;
left: 79%;
top: 1%;',
class = "plus",
shiny::img(src="metshi_gemmo.png",
id="metshiGem",
style='position: relative;
height: 100px;
top: 7%;
left: 88%;
z-index: 1005;'),
shiny::div(id="heartHolder",
style="left: 22%;
bottom: 4%;
position: relative;",
MetaboShiny::fadeImageButton("fancy",
img.path="metshi_heart.png",
value = F)
)
),
shinyjs::extendShinyjs(text = "shinyjs.closeWindow = function() { window.close(); }",
functions = c("closeWindow")),
shiny::div(id="loading-page",
style="position: fixed;
width: 200%;
height: 200%;
z-index: 4000;
background-color: black;
opacity: 0.6;
margin-left: -20px;",
div(id="load-img-holder",
class="imagetop",
style="left: 25%;
position: absolute;
top: 25%;
height:100px;
width:100px;
margin-top: -60px;
margin-left: -60px;",
div(id="loading-bg",
style="background-image: url(metshi_heart_bezel.png);
width:120px;
height:100px;")#,
# div(id="loading-fg",
# style="background-image: url(metshi_heart_full.png);
# z-index:4001;
# width:120px;
# transition: 1s height;
# height:0px;
# margin-top: -100px;")
)
),
shiny::div(
shiny::navbarPage(windowTitle='MetaboShiny',
# use this for title
# https://codepen.io/maxspeicher/pen/zrVKLE
title=shiny::div(id="appHeader",
class="outlined",
"MetaboShiny"), # make it use the sparkle.js for unnecessary sparkle effects ;)
id="nav_general",
# this tab shows the available databases, if they are installed, and buttons to install them. generated as output$db_build_ui in 'server'
shiny::tabPanel("database", icon = shiny::icon("database",
class = "outlined"),
value="database",
shiny::fluidRow(align="center", shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Settings"), value="panel4",
shiny::sliderInput(inputId = "db_mz_range", label = "What mass range can your machine detect?",
min = 0, max = 3000, value = c(60, 600),
step = 1,post = "m/z",dragRange = TRUE),
shiny::tags$i("Warning: increasing the upper m/z boundary may drastically increase database build times
- calculating isotopes is more time-consuming for larger molecules!"),
shiny::radioButtons("db_build_mode", label = "Build base database, extended (isotopes+adducts) or both?",
choices = c("base","extended","both"),selected = "both"),
shiny::tags$i("For example: if you only defined a new adduct, pick 'extended' as the source database doesn't change."),
shiny::helpText("Include minor isotopes?"),
shinyWidgets::switchInput(
inputId = "db_all_iso",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = T
),
shiny::helpText("Include heavy C, N, O count info for each isotope?"),
shinyWidgets::switchInput(
inputId = "db_count_iso",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = F
),
shiny::helpText("Queue multiple DB builds?"),
shinyWidgets::switchInput(
inputId = "db_build_multi",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = F
),
shiny::conditionalPanel("input.db_build_multi == true",
shiny::actionButton("db_build_sel_all",
label = "Select all"),
shiny::actionButton("db_build_multi_all",
label = "Build selected DBs",
icon=shiny::icon("wrench")))
)
)),
shiny::uiOutput("db_build_ui")
),
shiny::tabPanel("data import", icon = shiny::icon("upload", class = "outlined"),
# === NEW ===
shiny::fluidRow(align="center",
shiny::column(4,
shiny::icon("signature", class = "fa-8x"),
shiny::textInput("proj_name_new", label = "STEP 1: What is your project name?", value = ""),
shiny::icon("object-group", class = "fa-8x"),
br(),
br(),
shiny::tags$b("STEP 2: Click buttons to select files"),
br(),
br(),
div(shiny::uiOutput("wipe_regex_ui"), style='font-size:70%'),
shiny::fileInput(inputId = "metadata", "Select metadata", buttonLabel="Browse",accept = c(".csv",".tsv")),
#shinyFiles::shinyFilesButton('metadata', 'metadata', 'Select metadata', FALSE),
br(),
shinyWidgets::checkboxGroupButtons(
inputId = "ms_modes",
label = "Mass spec modes:",
choices = c(`<b class='fa fa-plus'> positive</b>` = "pos",
`<b class='fa fa-minus'> negative</b>` = "neg"),
selected = c("pos","neg"),
justified = F
),
shiny::uiOutput("outlist_pickers"),
shiny::div(shiny::imageOutput("proj_merge_check"), style="height:70px")),
shiny::column(4,
shiny::icon("bullseye", class = "fa-8x"),
shiny::numericInput("ppm", "STEP 3: What level accuracy does your mass spectrometer have?",min = 0.01,max = 50,value = 3),
shiny::helpText("Round m/z values based on ppm error?"),
shinyWidgets::switchInput(
inputId = "roundMz",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::icon("star-half-alt", class = "fa-8x"),
shinyWidgets::sliderTextInput("perc_limit_samp","STEP 4: What percentage missing m/z for a sample is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=100, grid = T)),
shiny::column(4,
shiny::icon("user-check", class = "fa-8x"),
shinyWidgets::sliderTextInput("perc_limit_mz","STEP 5: What percentage missing samples for a m/z value is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=80, grid = T),
shinyWidgets::actionBttn("checkMiss", label = "Check distribution (recommended)",size = "xs"),
shiny::plotOutput("missMzPlot"),
shiny::uiOutput("missMzRatio")
)),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::tags$b("STEP 6: Convert to input-ready format"),
shiny::br(),shiny::br(),
shinyWidgets::circleButton("create_csv", icon = shiny::icon("long-arrow-alt-right", class = "fa-2x"), size = "lg")),
shiny::fluidRow(align="center",
shiny::imageOutput("proj_csv_check", inline=T),shiny::br(),shiny::br(),
shiny::tags$b("STEP 7: If "), shiny::icon("check-circle"), shiny::tags$b(" continue to normalization"),
)
),
# this tab is used to perform normalization of your data. settings are processed as input$filt_type etc. in 'server'.
tabPanel("normalize", icon = shiny::icon("shower",class = "outlined"), value="filter",
shiny::fluidRow(align="center",shiny::column(3,
shiny::selectizeInput(width = "80%",'samp_var', 'Which variable represents sample amount/concentration?', choices = c(" ")), #TODO: only show this when normalize by sample specific factor (specnorm) is selected
shiny::selectizeInput('batch_var', 'What are your batch variables?', choices = c("batch"), multiple=TRUE, options = list(maxItems = 2L)),
shiny::selectizeInput(inputId = "batch_method_a",
label = "Batch correction method if machine batch and injection order are present:",
choices = list("WaveICA - WaveICA" = "waveica",
"BatchCorrMetabolomics - batchCorr" = "batchCorr",
"limma - removeBatchEffect" = "limma",
"ComBat" = "combat",
"CovBat" = "covbat"),
selected="waveica"),
shiny::selectizeInput(inputId = "batch_method_b",
label = "Batch correction method for other variables",
choices = list("limma - removeBatchEffect" = "limma",
"ComBat" = "combat",
"CovBat" = "covbat"),
selected="combat"),
shiny::actionButton("check_csv", "Get options", icon=shiny::icon("refresh")),
shiny::hr(),
shiny::selectizeInput(width = "80%",'filt_type', 'How will you filter your m/z values?', choices = list("Interquantile range" = "iqr",
"Relative stdev" = "rsd",
"Non-parametric relative stdev" = "nrsd",
"Mean" = "mean",
"Standard deviation" = "sd",
"Median absolute deviation" = "mad",
"Median" = "median",
"None" = "none"),
selected = "none"),
shiny::conditionalPanel("input.filt_type != 'none'",
shiny::numericInput(inputId="maxMz",
label = "Max. m/z to keep",
value = 5000)
),
shiny::selectizeInput(width = "80%",'norm_type', 'What type of normalization do you want to do?', choices = list("Quantile normalization" = "QuantileNorm",
"QCs per batch normalization" = "QcNorm",
"By reference feature" = "ProbNorm",
"By reference compound" = "CompNorm",
"By sample specific factor" = "SpecNorm",
"Sum" = "SumNorm",
"Median" = "MedianNorm",
"None" = "NULL"),
selected="QuantileNorm"),
# ref 289.18874-
shiny::conditionalPanel("input.norm_type == 'ProbNorm'",
div(shinyWidgets::pickerInput(
inputId = "ref_mz",
label = div(icon("search"), style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "click below button",
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker"),
shiny::actionButton("check_ref_mzs", "Get options", icon=shiny::icon("refresh"))
),
shiny::selectizeInput(width = "80%",'trans_type', 'How will you transform your data?', choices = list("Log transform" = "LogNorm",
"Cubic root transform" = "CrNorm",
"None" = "NULL"),
selected="LogNorm"),
shiny::selectizeInput(width = "80%",'scale_type', 'How will you scale your data?', choices = list("Autoscale/Z-transform" = "AutoNorm",
"Mean-center" = "MeanCenter",
"Pareto Scaling" = "ParetoNorm",
"Range scaling" = "RangeNorm",
"None" = "NULL"),
selected="AutoNorm"),
shinyWidgets::sliderTextInput("miss_perc_2","What percentage missing samples for a m/z is allowed?",
choices=c(0, 0.0001, 0.001, 0.01, 0.1, seq(1, 100, 1)),
selected=20, grid = T),
shiny::selectizeInput(width = "80%",'miss_type', 'How to deal with missing values?', choices = list("Half feature minimum" = "colmin",
"Half sample minimum" = "rowmin",
"Total minimum" = "min",
"Random forest" = "rf",
#"Impute w/ regression" = "regr",
"KNN imputation" = "knn",
"SVD imputation" = "svdImpute",
"BPCA imputation" = "bpca",
"PPCA imputation" = "ppca",
"Median" = "median",
"Mean" = "mean",
"Leave them out" = "exclude",
"Leave them alone" = "none"),
selected = "rowmin"),
shiny::conditionalPanel("input.miss_type == 'rf'",
shinyWidgets::switchInput("rf_norm_method", label = "Method:",
value = TRUE, onLabel = "missRanger",
offLabel="missForest",size = "small"),
shiny::sliderInput("rf_norm_ntree", label = "Trees built per variable", value = 10, min = 1, max = 50, step=1),
#numericInput("rf_norm_mtry", label = "Trees built per variable", value = 10, min = 1, max = 50)
shiny::radioButtons("rf_norm_parallel", label = "Parallelize?", choices = list("no",
"forests",
"variables"),
selected = "variables")
),
shinyWidgets::switchInput(
inputId = "redo_upon_change",
value = TRUE,
label = "Renormalize after subsetting?:",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
# - - - - - -
shinyWidgets::switchInput(
inputId = "pca_corr",
value = FALSE,
label = "PCA correction",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::conditionalPanel("input.pca_corr == true",
sliderInput("keep_pcs", label = h3("Keep variance in PCs:"), min = 0,
max = 300, value = c(10, 50))
),
MetaboShiny::switchButton(inputId = "remove_outliers",
label = "Exclude outliers?",
value = FALSE, col = "BW", type = "YN"),
shiny::actionButton("initialize", "Go", icon=shiny::icon("hand-o-right")),
br(),br(),br(),br()
), shiny::column(9,
# show the summary plots post-normalization
shiny::tabsetPanel(tabPanel("m/z values",# icon=shiny::icon("braille"),
shiny::fluidRow(shiny::column(6,
shiny::imageOutput("empty2",width="100%",height="1px"),
shiny::uiOutput("var1_wrap")),
shiny::column(6,
shiny::uiOutput("var3_wrap"))),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("var2_wrap")),
shiny::column(6,
shiny::uiOutput("var4_wrap")))
),
shiny::tabPanel("samples",# icon=shiny::icon("tint"),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("samp1_wrap")),
shiny::column(6,
shiny::uiOutput("samp3_wrap"))),
shiny::fluidRow(shiny::column(6,
shiny::uiOutput("samp2_wrap")),
shiny::column(6,
shiny::uiOutput("samp4_wrap")))
)
)
)
)),
shiny::tabPanel("prematch", icon = shiny::icon("search", class = "outlined"), value = "prematch",
# - - - pre-matching part - - -
shiny::fluidRow(align="center",
MetaboShiny::switchButton(inputId = "do_prematch",
label = "Do matching beforehand?",
col = "BW",
type = "YN"),
shiny::tags$i("All m/z values will be searched in the databases of choice and the results will be saved to your save file for fast access."),shiny::br(),
shiny::tags$i("Search results can still be overridden by manual searching. Don't forget to save after!")),
shiny::br(),
shiny::fluidRow(align="center",
shiny::column(2),
shiny::column(8, shiny::conditionalPanel("input.do_prematch == true",
shiny::h2("Included databases:"),
shiny::uiOutput("db_prematch_select"),
shinyWidgets::circleButton("select_db_prematch_all",
icon = shiny::icon("shopping-cart"),
size = "default")),
shiny::hr(),
shiny::fluidRow(shiny::column(6,shiny::h2("Find matches"),
shinyWidgets::circleButton(inputId = "prematch",
icon = shiny::icon("searchengin"))),
shiny::column(6,shiny::h2("Clear matches"),
shinyWidgets::circleButton(inputId = "clear_prematch",
icon = shiny::icon("trash"))))
),
shiny::column(2)
)),
# this tab is the main analysis tab. all tabs for all analyses are listed here, but the visibility is changed depending on the current experiment
shiny::tabPanel("analyse", icon = shiny::icon("bar-chart",class = "outlined"), value = "analysis",
div(id="panelContainer",sidebarLayout(position="right",
mainPanel = #shinyjqui::jqui_resizable(
mainPanel(width = 9, id="mainPanel",
shiny::fluidRow(align="center",
shiny::imageOutput("empty3",width="100%",height="1px"),
shinyBS::bsCollapse(id = "collapse_summary",
shinyBS::bsCollapsePanel(title = tags$b(icon("caret-down"), "show/hide selected m/z abundance", icon("caret-down")),
style = "info",
shiny::uiOutput("summary_plot_wrap"))
)),
shiny::tabsetPanel(id="statistics", selected = "inf",
# TODO: T-SNE
# this tab shows general information, mostly a message with 'please give me some data' :-)
shiny::tabPanel("start", icon = shiny::icon("star", "fa-2x"), value = "inf",
shiny::fluidRow(align="center", shiny::column(width=12,
shiny::br(),shiny::br(),shiny::br(),shiny::br(),
#shiny::hr(),
#shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"),
shiny::br(),shiny::br(),
shiny::h2("Please select a variable of interest in the sidebar!"),shiny::br(),
shiny::icon("exchange", "fa-4x"),
shiny::h2("Alternatively, load an existing dataset from the bottom toolbar."),shiny::br(),
shiny::icon("folder-open", "fa-4x"),
shiny::br(),shiny::br(),shiny::br()
#shiny::hr()
#shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg"), shiny::icon("arrow-right","fa-lg")
))),
shiny::navbarMenu("dimension reduction", icon=icon("cube", "fa-2x"),menuName = "dimred",
shiny::tabPanel("pca", value = "pca",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id = "collapse_pca",
shinyBS::bsCollapsePanel(title = h2("settings"),
value = "collapse_pca_settings",
shinyWidgets::radioGroupButtons("pca_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
shinyWidgets::actionBttn(
inputId = "do_pca",
label = "click to start PCA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_pca_plots",
shiny::tabsetPanel(shiny::tabPanel("samples",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_pca_wrap")
))),
shiny::tabPanel("loadings",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_pca_loadings_wrap"))
))),
fluidRow(align="center",
br(),
shinyWidgets::switchInput(
inputId = "pca_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "pca_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("pca_x", label = "X axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
},
selected = 1,width="80%")),
column(4,shiny::selectizeInput("pca_y", label = "Y axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("pca_z", label = "Z axis:", choices =
{
n = paste0("PC",1:500)
l = as.list(c(1:500))
names(l) = n
l
}, selected = 3,width="80%")))
)),
shinyBS::bsCollapsePanel(title = h2("tables"),value = "collapse_pca_tables",shiny::tabsetPanel(id="pca_2",
shiny::tabPanel(title="table",
shiny::div(DT::dataTableOutput('pca_tab',width="100%"),style='font-size:80%')),
shiny::tabPanel(title="scree",
shiny::uiOutput("pca_scree_wrap")
),
shiny::tabPanel(title="loadings",
shiny::div(DT::dataTableOutput('pca_load_tab',width="100%"),style='font-size:80%'))
)),open = 1)
)
),
shiny::tabPanel("pls-da", value = "plsda",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_plsda",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_plsda_settings",
shiny::fluidRow(align = "center",
shiny::div(style="display:inline-block",
shiny::selectizeInput("plsda_type",
label="Type:",
choices=list("Normal" = "normal")
#,
# "Orthogonal" = "ortho",
# "Sparse" = "sparse")
,width = '100px',
selected=1)),br(),
shinyWidgets::actionBttn(
inputId = "do_plsda",
label = "click to start PLS-DA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_plsda_plots",
shiny::tabsetPanel(shiny::tabPanel("samples",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_plsda_wrap")))),
shiny::tabPanel("loadings",
shiny::fluidRow(align="center",shiny::column(12,
shiny::uiOutput("plot_plsda_loadings_wrap")
))),
shiny::tabPanel("performance",
shiny::tabsetPanel(id="plsda_2",
shiny::tabPanel(title="cross-validation",
shiny::uiOutput("plsda_cv_plot_wrap")),
shiny::tabPanel(title="permutation",
shiny::uiOutput("plsda_perm_plot_wrap")))
)),
fluidRow(align="center",
br(),
shinyWidgets::switchInput(
inputId = "plsda_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "plsda_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("plsda_x", label = "X axis:", choices =
{
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("plsda_y", label = "Y axis:", choices = {
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("plsda_z", label = "Z axis:", choices = {
n = paste("Component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_plsda_tables",
shiny::tabPanel(title="scree",
shiny::div(DT::dataTableOutput('plsda_tab',width="100%"),style='font-size:80%')),
shiny::tabPanel(title="loadings",
shiny::div(DT::dataTableOutput('plsda_load_tab',width="100%"),style='font-size:80%')))
))
),
shiny::tabPanel("t-sne", value = "tsne",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_tsne",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_tsne_settings",
shinyWidgets::radioGroupButtons("tsne_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
numericInput("tsne_dims", "Initial dimensions:", min = 5, step = 1, value = 30),
numericInput("tsne_perplex", "Perplexity:", min = 5, value = 30),
numericInput("tsne_maxiter", "Max iterations:", min = 10, value = 100),
shinyWidgets::actionBttn(
inputId = "do_tsne",
label = "click to start t-SNE",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_tsne_plots",
shiny::uiOutput("tsne_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "tsne_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "tsne_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("tsne_x", label = "X axis:", choices =
{
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("tsne_y", label = "Y axis:", choices = {
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("tsne_z", label = "Z axis:", choices = {
n = paste("t-sne component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
),
shiny::tabPanel("ica", value = "ica",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_ica",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_ica_settings",
shinyWidgets::radioGroupButtons("ica_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
numericInput("ica_ncomp", "Components calculated:", min = 2, step = 1, value = 3),
numericInput("ica_maxiter", "Max iterations:", min = 10, value = 100),
shinyWidgets::radioGroupButtons(
inputId = "ica_method",
label = "Method:",
choices = c("fast",
"imax", "jade"
),
justified = TRUE,selected="fast",
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"))
),
shinyWidgets::actionBttn(
inputId = "do_ica",
label = "click to start ICA (independant component analysis)",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_ica_plots",
shiny::uiOutput("ica_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "ica_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "ica_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("ica_x", label = "X axis:", choices =
{
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("ica_y", label = "Y axis:", choices = {
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("ica_z", label = "Z axis:", choices = {
n = paste0("IC",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
),
shiny::tabPanel("umap", value = "umap",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id = "collapse_umap",
multiple=T,shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_umap_settings",
shinyWidgets::radioGroupButtons("umap_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
sliderInput("umap_ncomp", "Components calculated:", min = 2, max = 20, step = 1, value = 3),
numericInput("umap_maxiter", "Max iterations:", min = 10, value = 100),
numericInput("umap_neighbors", "Neighbors used", value = 15),
shinyWidgets::actionBttn(
inputId = "do_umap",
label = "click to start UMAP",
style = "bordered",
icon = icon("terminal"),
size = "sm"
))
,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_umap_plots",
shiny::uiOutput("umap_plot_wrap"),
br(),
shiny::conditionalPanel("input.ggplotly == true",
shinyWidgets::switchInput(
inputId = "umap_2d3d",
size = "mini",
onLabel = "2D",
offLabel = "3D",
value = TRUE
)),
helpText("show ellipses"),
shinyWidgets::switchInput(
inputId = "umap_ellipse",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
fluidRow(column(4,shiny::selectizeInput("umap_x", label = "X axis:", choices =
{
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 1,width="80%")),
column(4,shiny::selectizeInput("umap_y", label = "Y axis:", choices = {
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 2,width="80%")),
column(4,shiny::selectizeInput("umap_z", label = "Z axis:", choices = {
n = paste("UMAP component",1:20)
l = as.list(c(1:20))
names(l) = n
l
},selected = 3,width="80%")))
)))
)
),
shiny::navbarMenu("per m/z", icon=shiny::icon("fingerprint", "fa-2x"), menuName = "permz",
shiny::tabPanel("t-test", value="tt",
shiny::fluidRow(align="center",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_tt",
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_tt_settings",
MetaboShiny::switchButton("tt_nonpar", "Non-parametric?", col="BW", type="YN", value = T),
MetaboShiny::switchButton("tt_eqvar", "Equal variance?", col="BW", type="YN", value = T),
shiny::selectInput("tt_multi_test", "Multiple testing correction method:",
choices = list("Holm"="holm",
"Hochmerg"="hochberg",
"Hommel"="hommel",
"Bonferroni"="bonferroni",
"Benjamini & Hochberg"="fdr",
"Benjamini & Yekutieli"="BY",
"none"),
selected = "fdr"),
shiny::numericInput("tt_p_thresh",
label = "Maximum p-value after multiple testing:",
value=0.05,max = 1, min=0),
shinyWidgets::actionBttn(
inputId = "do_tt",
label = "click to start t-test",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_tt_plots",
shiny::uiOutput("tt_plot_wrap"),
shiny::sliderInput('tt_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_tt_tables",
shiny::div(DT::dataTableOutput('tt_tab',width="100%"),style='font-size:80%')
))
)
)),
shiny::tabPanel("anova", value="aov",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_aov",
multiple = T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_aov_settings",
shinyWidgets::actionBttn(
inputId = "do_aov",
label = "click to start ANOVA",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_aov_plots",
shiny::uiOutput("aov_plot_wrap"),
shiny::sliderInput('aov_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_aov_tables",
shiny::div(DT::dataTableOutput('aov_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("fold-change", value="fc",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_fc",multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_fc_settings",
shiny::sliderInput("fc_thresh", "Fold-change threshold:",
min=0,
max=10,
value = 1.2,
step = 0.1),
shinyWidgets::actionBttn(
inputId = "do_fc",
label = "click to start fold-change analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_fc_plots",
shiny::uiOutput("fc_plot_wrap"),
shiny::sliderInput('fc_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_fc_tables",
shiny::div(DT::dataTableOutput('fc_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("meba", value="meba",
shiny::fluidRow(align="center",shinyBS::bsCollapse(id="collapse_meba", multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_meba_settings",
shinyWidgets::actionBttn(
inputId = "do_meba",
label = "click to start MEBA analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_meba_plots",
shiny::uiOutput("meba_plot_wrap"),
shiny::sliderInput('meba_topn',label = "Show top:",min = 5,max=5000,value = 100)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_meba_tables",
shiny::div(DT::dataTableOutput('meba_tab', width="100%"),style='font-size:80%')
)
)
)
),
shiny::tabPanel("asca", value="asca",
shiny::fluidRow(align="center",shinyBS::bsCollapse(id="collapse_asca", multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_asca_settings",
shinyWidgets::actionBttn(
inputId = "do_asca",
label = "click to start ASCA analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_asca_plots",
shiny::uiOutput("asca_plot_wrap")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_asca_tables",
shiny::div(DT::dataTableOutput('asca_tab', width="100%"),style='font-size:80%')
)
)
)
),
shiny::tabPanel("pattern", value="corr",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_corr",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_corr_settings",
uiOutput('jqui_ui'), br(),
shiny::selectizeInput("corr_corr",
"Correlation metric:",
choices = c("pearson", "spearman", "kendall"),
selected = "spearman"),
# corr_p_thresh corr_r_thresh
shiny::numericInput("corr_p_thresh",
label = "Maximum p-value:",
value=0.1),
shiny::numericInput("corr_r_thresh",
label = "Minimum correlation (absolute):",
value=0.1),
shinyWidgets::actionBttn(
inputId = "do_corr",
label = "click to start pattern finding",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_corr_plots",
shiny::uiOutput("corr_plot_wrap"),
shiny::sliderInput('corr_topn',label = "Show top:",min = 5,max=200,value = 20)
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_corr_tables",
shiny::div(DT::dataTableOutput('corr_tab',width="100%"),style='font-size:80%')
))
)
)
),
shiny::navbarMenu("overview analyses", icon=shiny::icon("globe", "fa-2x"), menuName = "overview",
shiny::tabPanel("intersection plot", value="combi",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T, id="collapse_combi",
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_combi_settings",
shiny::fluidRow(align="center",
column(6, shiny::selectizeInput("combi_anal1",label = "X-axis:", choices=c()),
shiny::uiOutput("combi_anal1_picker"),
shiny::selectizeInput("combi_anal1_trans",label = "Transformation:", choices=c(
"none",
"log10",
"-log10",
"abs"
),selected = "none")
),
column(6, shiny::selectizeInput("combi_anal2",label = "Y-axis:", choices=c()),
shiny::uiOutput("combi_anal2_picker"),
shiny::selectizeInput("combi_anal2_trans",label = "Transformation:", choices=c(
"none",
"log10",
"-log10",
"abs"
),selected = "none"))
),
shinyWidgets::actionBttn(
inputId = "do_combi",
label = "click to make combi plot",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_combi_plots",
shiny::uiOutput("combi_plot_wrap")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_combi_tables",
shiny::div(DT::dataTableOutput('combi_tab',width="100%"),style='font-size:80%')
))
)
),
shiny::tabPanel("heatmap", value="heatmap",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_heatmap_settings",
shiny::selectizeInput("heattable",
"Use which analysis?",
choices = c("none available"),
selected = 1,
multiple = F),
MetaboShiny::switchButton("heatsign", label = "Only significant hits?", col = "GB", type = "YN"),
MetaboShiny::switchButton("heatlimits", label = "Color based on -all- metabolites?", col = "GB", type = "YN"),
shinyWidgets::radioGroupButtons("heatmap_source", "Used data:", choices = c("original",
"pre-batch correction",
"normalized"),
selected="normalized"),
shinyWidgets::actionBttn(
inputId = "do_heatmap",
label = "click to make heatmap",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_heatmap_plots",
shiny::verbatimTextOutput("heatmap_now", placeholder = F),
shiny::uiOutput("heatmap_plot_wrap"),
shiny::sliderInput("heatmap_topn",
label = "Show top:",
min = 10,
max = 5000,
step=10,
value=20)
))
)
),
shiny::tabPanel("network", value="network",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),
value="collapse_network_settings",
shinyWidgets::switchInput("network_sel",
"Include",
value = TRUE,
onLabel="all",
offLabel="subset"),
shiny::conditionalPanel("input.network_sel == false",
shiny::selectizeInput("network_table",
"Use which analysis?",
choices = c("none available"),
selected = 1,
multiple = F),
shiny::sliderInput("network_topn",
label = "Use top m/z:",
min = 10,
max = 5000,
step=10,
value=20)
),
shiny::numericInput("network_sign",
label = "p-value threshhold",
value = 0.05,
min = 0.0000001,
max = 1),
shinyWidgets::switchInput("network_auto",
"Network style",value = T,
onLabel = "auto",
offLabel = "choose"),
shiny::conditionalPanel("input.network_auto == false",
shiny::selectizeInput("network_style", "Style:",
choices = list("Hierarchical" = "hierarchical",
"Circular" = "layout_in_circle",
"Nicely" = "layout_nicely",
"Sugiyama" = "layout_with_sugiyama",
"Star" = "layout_as_star",
"Tree" = "layout_as_tree",
"Grid" = "layout_on_grid",
"Sphere" = "layout_on_sphere",
"Randomly" = "layout_randomly",
"DH" = "layout_with_dh",
"FR" = "layout_with_fr",
"Gem" = "layout_with_gem",
"Graphopt" = "layout_with_graphopt",
"KK" = "layout_with_kk",
"LGL" = "layout_with_lgl",
"MDS" = "layout_with_mds"
))),
shiny::selectizeInput("network_corr",
label = "Correlation method:",
choices = c("pearson", "kendall", "spearman"),
multiple = F,
selected = "pearson"
),
shinyWidgets::actionBttn(
inputId = "do_network",
label = "click to make network",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_network_plots",
shiny::verbatimTextOutput("network_now", placeholder = F),
shiny::tabsetPanel(id="network_results",
shiny::tabPanel(title = "network",value = "network",
icon=shiny::icon("project-diagram"),
shiny::fluidRow(align="center",shiny::uiOutput("network_wrap")),
),
shiny::tabPanel(title = "heatmap",value = "heatmap",
icon=shiny::icon("th"),
shiny::fluidRow(align="center",shiny::uiOutput("network_heatmap_wrap")),
))
))
)
),
# this tab is used to find overlapping features of interest between analyses
# TODO: enable this with multiple saved mSets in mSet$storage
shiny::tabPanel(title="venn", value="venn", #icon=shiny::icon("comments"),
br(),
sidebarLayout(position = "left",
sidebarPanel = shiny::sidebarPanel(width = 4,
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_unselected'),style='font-size:80%'), align="center"),
shiny::fluidRow(shinyWidgets::circleButton("venn_add", icon=shiny::icon("arrow-down"), size="sm"),
shinyWidgets::circleButton("venn_remove", icon=shiny::icon("arrow-up"), size="sm"),
align="center"),
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_selected'),style='font-size:80%'),align="center"),
shiny::hr(),
shiny::selectizeInput("venn_filter_mode",label = "Use top hits or an absolute threshold?",
choices = c("top", "threshold"),selected = "top"),
shiny::conditionalPanel("input.venn_filter_mode == 'threshold'",
shiny::uiOutput("venn_threshold_ui")
),
shiny::conditionalPanel("input.venn_filter_mode == 'top'",
shiny::fluidRow(
shiny::sliderInput("venn_tophits", label = "Only include top:", min = 1, max = 200, post = " hits", value=20)
,align="center")),
shinyWidgets::switchInput(
inputId = "venn_plot_mode",
value = FALSE,
label = "Plot type",
onLabel = "upset",
offLabel = "venn",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::fluidRow(
shinyWidgets::actionBttn(
inputId = "venn_build",
label = "click to make venn diagram",
style = "bordered",
icon = icon("terminal"),
size = "sm"
),align="center")
),
mainPanel = mainPanel(
shiny::hr(),
shiny::uiOutput("venn_plot_wrap"),
# find the overlapping compounds between the groups you want to compare (user select)
# TODO: enable this with clicking the numbers/areas
shiny::fluidRow(shiny::selectizeInput(width = "80%","intersect_venn", label = "Show hits from (only):", selected = 1,choices = "",multiple = T),
align="center"),
shiny::fluidRow(shiny::uiOutput("venn_pval"), align="center"),
shiny::br(),
shiny::fluidRow(shiny::div(DT::dataTableOutput('venn_tab'),style='font-size:80%'),
align="center")
))
),
shiny::tabPanel("power calculation", value="power",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(multiple=T,id="collapse_power",shinyBS::bsCollapsePanel(title = h2("settings"),value="collapse_power_settings",
shiny::sliderInput("power_nsamp",
label = "Up to how many samples (per group)?",
value = 500,
min = 5,
max = 999,
step = 1),
shiny::selectizeInput("power_comps", "Which comparisons do you want to make?",
choices = c(" "),
multiple = T),
shiny::numericInput("power_fdr", "False discovery rate:",
value = 0.1,
max = 1,
min = 0.00001),
shinyWidgets::actionBttn(
inputId = "do_power",
label = "click to start power analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)),
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_power_plots",
shiny::uiOutput("power_plot_wrap")
)
))
),
shiny::tabPanel("enrichment", value = "enrich",
sidebarLayout(position = "left",
sidebarPanel = sidebarPanel(
shiny::fluidRow(align="center",
h3("Enrichment parameters"),
shiny::selectizeInput("mummi_org",
label = "Pathway KEGG database:",
choices = list(
"Homo sapiens (human)"="hsa01100",
"Sus scrofa (swine)"="ssc01100",
"Microbial metabolism in diverse environments"="map01120",
"Bos taurus (cow)"="bsa01100",
"Mus musculus (mouse)"="mmu01100",
"Rattus norvegicus (rat)"="rno01100",
"Danio rerio (zebrafish)"="dre01100",
"Caenorhabditis elegans (nematode)"="cel01100",
"Gallus gallus (chicken)"="gga01100",
"Escherichia coli K-12 MG1655"="eco01100"
), selected = "hsa01120",options = ),# REGEX: [:|"|,][A-z]+?_[A-z]+?[:|"|,] ON the metaboanalyst page showing the table with options
shinyWidgets::switchInput(
inputId = "mummi_enr_method",value = TRUE,
onLabel = "mummichog",
offLabel = "gsea"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shinyWidgets::switchInput(
inputId = "mummi_rules",
value = FALSE,
onLabel = "yes",
label = "Apply adduct rules?",
offLabel = "no"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::textInput("mummi_pval", label = "Required p-value:", value = "0.005"),
br(),
h3("User data parameters"),
shiny::selectizeInput("mummi_anal",
"Use analysis:",
choices = c("none available"),
selected = 1,
multiple = F),
shiny::sliderInput("mummi_topn",
"Top hits used:",
min = 10,
max = 5000,
step = 1,
value = 100),
shinyWidgets::pickerInput(inputId = "mummi_adducts",
choices = adducts$Name,
label = "Adducts to look for:",
selected = c("[M+H]1+", "[M+Na]1+", "[M+2H]2+", "[M+K]1+"),
multiple = T,
options = list(
`actions-box` = TRUE)),
shiny::uiOutput("mummi_adducts_cats"),
shinyWidgets::actionBttn(
inputId = "do_enrich",
label = "click to start enrichment analysis",
style = "bordered",
icon = icon("terminal"),
size = "sm"
)
)),
mainPanel = mainPanel(fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_enrich",multiple=T,
shinyBS::bsCollapsePanel(title = h2("plots"),value="collapse_enrich_plots",
shiny::tabsetPanel(id = "enrich_results",
shiny::tabPanel("overview",
shiny::uiOutput("enrich_plot_wrap"),
shinyWidgets::switchInput("enrich_plot_mode", "Plot type:",
onLabel = "point", offLabel = "bar",
value = T),
shinyWidgets::switchInput("enrich_sig_only","Only color significant hits?",
onLabel = "yes", offLabel = "no",
value = F),
),
shiny::tabPanel("selected pathway",
shinyWidgets::switchInput("enrich_pathway_plot_mode", "Style:",
onLabel="kegg",
offLabel="generic", value=T),
shiny::actionButton("enrich_plot_pathway", "Plot pathway"),
shiny::wellPanel(id = "pathway_panel",
style = "overflow-y:scroll; overflow-x:scroll; max-height: 600px",
imageOutput("enrich_pathway"))
))
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_enrich_tables",
shiny::div(DT::dataTableOutput("enrich_tab",
width="100%"),
style='font-size:80%'),
shiny::div(DT::dataTableOutput("enrich_pw_tab",
width="100%"),
style='font-size:80%'))
)
))
)
),
# PUT IT HERE
shiny::tabPanel("feature selection",
value="featsel",
shiny::fluidRow(align="center",
shinyBS::bsCollapse(id="collapse_featsel",
multiple=T,
shinyBS::bsCollapsePanel(title = h2("settings"),
value="collapse_featsel_settings",
shinyWidgets::actionBttn(
inputId = "do_featsel",
label = "click to start Boruta feature selection",
style = "bordered",
icon = icon("terminal"),
size = "sm")
),
shinyBS::bsCollapsePanel(title = h2("tables"),value="collapse_featsel_tables",
shiny::div(DT::dataTableOutput('featsel_tab',
width="100%"),
style='font-size:80%')
)
)
))
),
shiny::tabPanel("machine learning",
value = "ml", icon=shiny::icon("signature", "fa-2x"),
shiny::br(),
shiny::tabsetPanel(id = "ml2",
shiny::tabPanel("configure",icon = icon("cog"),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shiny::tags$h3("Job name"),
shiny::icon("signature", "fa-3x"),
shiny::textInput("ml_name",
label="",
value = stringi::stri_rand_strings(1,
10,
pattern = "[A-Za-z0-9]"))
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width = 3,
shiny::tags$h3("Input data"),
shiny::icon("table", "fa-3x"),
hr(),
shinyBS::bsCollapse(
shinyBS::bsCollapsePanel("Used data",
shiny::selectizeInput("ml_used_table",
label = "Used data:",
choices = list("orig", "prebatch", "norm", "pca"),
selected = "norm"),
shiny::selectizeInput("ml_include_covars",
label = "Use which metadata for prediction?",
choices=c(" "), multiple=TRUE)
),
shinyBS::bsCollapsePanel("Used samples",
shiny::selectizeInput("ml_samp_distr", label = "Reuse train/test sample distribution from previous experiment?",
choices=c(" "), multiple=FALSE),
shiny::conditionalPanel("input.ml_samp_distr == ' '",
shiny::selectInput("ml_tr_te_subset",
"Train or test on a metadata-based subset of the data?",
choices = c("yes","no")),
shiny::conditionalPanel("input.ml_tr_te_subset == 'yes'",
shiny::helpText("Train on subset:"),
shiny::fluidRow(sardine(shiny::textOutput("ml_train_ss")),
shinyWidgets::circleButton(inputId = "reset_ml_train",
icon=shiny::icon("undo"),
size = "xs",
status = "warning"),br(),
shinyWidgets::circleButton("ml_train_ss", label = ":",
icon = shiny::icon("arrow-left"))),
shiny::helpText("Test on subset:"),
shiny::fluidRow(sardine(shiny::textOutput("ml_test_ss")),
shinyWidgets::circleButton(inputId = "reset_ml_test",
icon=shiny::icon("undo"),
size = "xs",
status = "warning"),br(),
shinyWidgets::circleButton("ml_test_ss",
icon = shiny::icon("arrow-left")))
),
shiny::conditionalPanel("input.ml_tr_te_subset == 'no'",
shiny::sliderInput("ml_train_perc",
label = "Percentage of samples in training",
min = 1,
max = 100,
step = 1,
value = 80,
post = "%"))
)
),
shinyBS::bsCollapsePanel("Used m/z",
shiny::selectizeInput("ml_specific_mzs", label = "Analysis-based top hits", choices=c(" "), multiple=FALSE),
shiny::conditionalPanel("input.ml_specific_mzs != 'no'",
shiny::conditionalPanel("input.ml_specific_mzs == 'manual'",
div(shinyWidgets::pickerInput(
inputId = "ml_mzs",
label = div(icon("search"),
style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "fa-cat",
multiple = T,
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker")),
shiny::conditionalPanel("input.ml_specific_mzs != 'manual'",
shiny::sliderInput('ml_mzs_topn',
label = "Use top:",min = 1,max=200,value = 20),
shinyWidgets::switchInput("ml_mzs_rand",
label = "Randomize order?",
value = F,
onLabel = "yes",
offLabel = "no"),
shiny::textOutput("ml_specific_mzs_sigcount")
)
)
)
)
),
shiny::column(width = 1,
shiny::icon("caret-right", "fa-5x vertical-center")
),
shiny::column(width = 3,
shiny::tags$h3("Data adjustment"),
shiny::icon("shower", "fa-3x"),
hr(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Batch correction",
value="ml_batch_panel",
shiny::selectizeInput("ml_batch_covars", label = "Batch metadata column:",
choices=c(" "),
multiple=F),
shiny::helpText("Balance classes per batch factor?"),
shinyWidgets::switchInput(
inputId = "ml_batch_balance",
value = FALSE,
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::helpText("If batch present, make all batches same size in TOTAL? Otherwise each batch will have the right percentage train/test but one batch may be larger than another in TOTAL.:"),
shinyWidgets::switchInput(
inputId = "ml_batch_size_sampling",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = FALSE
),
shiny::conditionalPanel("input.ml_batch_size_sampling == true",
shiny::numericInput("ml_groupsize",
label = "Size per experimental group (auto: 0):",
value = 0)))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Class balancing",
shinyWidgets::radioGroupButtons(
inputId = "ml_sampling",
label = "How to balance class labels?:",
choices = c(`<i class='fa fa-arrow-down'></i> downsample` = "down",
`ROSE` = "rose",
`SMOTE` = "smote",
`ADASYN` = "adasyn",
`don't` = "none",
`upsample <i class='fa fa-arrow-up'></i>` = "up"),
justified = FALSE,
selected = "none"
)
)),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Miscellanaous",
shiny::selectizeInput("ml_preproc", label = "Data preprocessing",
choices = c("center", "scale"),
selected = c(), multiple=T),
shinyWidgets::switchInput(
inputId = "ml_pca_corr",
value = FALSE,
label = "PCA correction",
onLabel = "yes",
offLabel = "no",
size = "small"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::conditionalPanel("input.ml_pca_corr == true",
sliderInput("ml_keep_pcs",
label = "Keep variance in PCs:",
min = 0,
max = 300, value = c(10, 50))
)
))
),
shiny::column(width = 1,
shiny::icon("caret-right", "fa-5x vertical-center")
),
shiny::column(width = 3,
shiny::tags$h3("Model settings"),
shiny::icon("sliders-h", "fa-3x"),
hr(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Algorithm",
shiny::selectizeInput("ml_method",
label = "Used algorithm",
selected = "glmnet",
choices = as.list(gbl$constants$ml.models),
multiple = F),
shiny::div(shiny::uiOutput("ml_params"), style = "font-size:60%"))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title = "Cross validation",
shiny::selectizeInput("ml_perf_metr",
label="Performance metric",
choices = c("boot", "boot632", "optimism_boot",
"boot_all", "cv", "repeatedcv",
"LOOCV", "LGOCV", "none", "oob",
"timeslice", "adaptive_cv",
"adaptive_boot","adaptive_LGOCV"),
multiple = F, selected = "cv"),
shiny::selectizeInput("ml_folds", label="Fold CV",choices = c("5",
"10",
"20",
"50",
"LOOCV"),
multiple = F))),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Significance",
shiny::helpText("Calculate p-value using shuffled labels?"),
shinyWidgets::switchInput(
inputId = "ml_label_shuffle",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = FALSE
),
shiny::conditionalPanel("input.ml_label_shuffle == true",
shiny::numericInput("ml_n_shufflings",
"Number of randomized models:",
value=1, min=1, max=NA),
shiny::helpText("Shuffle train or testing labels?"),
shinyWidgets::switchInput(
inputId = "ml_shuffle_mode",
value = TRUE,
onLabel = "train",
offLabel = "test",
size = "small")
)))
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shinyWidgets::actionBttn(
inputId = "queue_ml",
label = "add to queue",
style = "bordered",
icon = icon("plus"),
size = "sm"
),
shinyWidgets::actionBttn(
inputId = "queue_ml_del",
label = "remove from queue",
style = "bordered",
icon = icon("minus"),
size = "sm"
))
),
br(),
shiny::fluidRow(align="center",
shiny::column(width = 11,
shinyWidgets::actionBttn(
inputId = "do_ml",
label = "start ML queue",
style = "bordered",
icon = icon("terminal"),
size = "l"
)
)
),
shiny::hr(),
shiny::fluidRow(align="center",
shiny::column(width=6,
shiny::tags$h3("Job queue"),
shiny::icon("list-ol", "fa-3x"),
br(),br(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title="Advanced",
value="ml_queue_panel",
shiny::textInput("queue_ml_name",
label = "Queue (file) name:",
value = "my_queue"),
shinyWidgets::actionBttn(
inputId = "queue_ml_save",
label = "save queue",
style = "bordered",
icon = icon("terminal"),
size = "sm"
),
shiny::fileInput(
inputId = "queue_ml_load",
label = "load queue"
))),
DT::DTOutput("ml_queue_all")),
shiny::column(width=5,
shiny::tags$h3("Job settings"),
shiny::icon("cogs","fa-3x"),
shiny::br(), shiny::br(),
DT::DTOutput("ml_queue_sel"))
)
),
shiny::tabPanel("results", value="res",icon = icon("chart-area"),
shiny::fluidRow(align="center",
shiny::selectizeInput("show_which_ml",
label = "Plot which model?",
choices = c(" ")),
shiny::actionButton("clear_ml_runs", "clear results", icon=icon("broom"))),
shiny::tabsetPanel(id="ml_results",
shiny::tabPanel(title = "curves",value = "roc",icon=shiny::icon("area-chart"),
shiny::fluidRow(align="center",shiny::uiOutput("ml_roc_wrap")),
shiny::fluidRow(align="center",
shiny::column(4,
shiny::selectizeInput("ml_plot_posclass",
label = "Positive class",
choices = c("placeholder"),
selected=c("placeholder")
)
),
shiny::column(3,
shiny::selectizeInput("ml_plot_x",
"Metric for x axis:",
choices = list("Accuracy"="acc",
"Error rate"="err",
"False positive rate"="fpr",
"True positive rate"="tpr",
"Fallout"="fall",
"Recall"="rec",
"Sensitivity"="sens",
"False negative rate"="fnr",
"Miss"="miss",
"True negative rate"="tnr",
"Positive predictive value"="ppv",
"Precision"="prec",
"Negative predictive value"="npv",
"Precision-conditioned fallout"="pcfall",
"Precision-conditioned miss"="pcmiss",
"Rate of positive predictions"="rpp",
"Rate of negative predictions"="rnp",
"Phi correlation coefficient"="phi",
"Matthews' corelation coefficient"="mat",
"Mutual information"="mi",
"Chi square test statistic"="chisq",
"Odds ratio"="odds",
"Lift value"="lift",
"Precision-recall F value"="f",
"Cutoff"="cutoff"),
selected = "fpr")),
shiny::column(3,
shiny::selectizeInput("ml_plot_y",
"Metric for y axis:",
choices = list("Accuracy"="acc",
"Error rate"="err",
"False positive rate"="fpr",
"True positive rate"="tpr",
"Fallout"="fall",
"Recall"="rec",
"Sensitivity"="sens",
"False negative rate"="fnr",
"Miss"="miss",
"True negative rate"="tnr",
"Positive predictive value"="ppv",
"Precision"="prec",
"Negative predictive value"="npv",
"Precision-conditioned fallout"="pcfall",
"Precision-conditioned miss"="pcmiss",
"Rate of positive predictions"="rpp",
"Rate of negative predictions"="rnp",
"Phi correlation coefficient"="phi",
"Matthews' corelation coefficient"="mat",
"Mutual information"="mi",
"Chi square test statistic"="chisq",
"Odds ratio"="odds",
"Lift value"="lift",
"Precision-recall F value"="f",
"Cutoff"="cutoff"),
selected = "tpr")),
column(2, actionButton(inputId = "reload_ml_stats", "Go"))),
fluidRow(
shiny::column(6, shiny::div(DT::dataTableOutput("ml_overview_tab",
width="100%"),
style='font-size:80%')),
shiny::column(6, shiny::plotOutput("conf_matr_plot"))
)
),
# shiny::tabPanel("mistakes & metadata",value="bar",icon=shiny::icon("times"),
# shiny::fluidRow(align="center",shiny::uiOutput("ml_mistake_wrap"),
# shiny::selectizeInput("ml_mistake_var",
# label = "Check percentage mistaken for which metadata column?",
# choices = "",
# multiple = F),
# shinyWidgets::switchInput(
# inputId = "ml_mistake_smooth",
# size = "small",
# onLabel = "smoothed",
# offLabel = "raw",
# value = F
# ),
# shinyWidgets::switchInput(
# inputId = "ml_mistake_per_rep",
# size = "small",
# onLabel = "per repeat",
# offLabel = "average repeats",
# value = FALSE
# ),
# shinyWidgets::actionBttn(
# inputId = "plot_ml_mistake",
# label = "click to plot",
# style = "bordered",
# icon = icon("pencil-alt"),
# size = "sm"
# ))
# ),
shiny::tabPanel("importance",value="bar",icon=shiny::icon("star"),
shiny::fluidRow(align="center",
shiny::uiOutput("ml_bar_wrap"),
shiny::sliderInput("ml_topn",
label = "Show top:",
min = 10,
max = 200,
step=10,
value=20),
shiny::div(DT::dataTableOutput("ml_importance_tab",
width="100%"),
style='font-size:80%')
)
),
shiny::tabPanel("used settings", value="param", icon=shiny::icon("cog"),
shiny::div(DT::dataTableOutput("ml_param_tab",
width="50%"))
)
)
))
))
),
# this is the sidebar that shows in the analysis tab. contains a lot of settings on the current variable of interest, plot themes and colours, and venn diagrams.
sidebarPanel =
shinyjqui::jqui_resizable(
sidebarPanel(align="center",width = 3,id="sidePanel",
shiny::fluidRow(align="center",
shiny::tabsetPanel(id = "anal_sidebar", selected="start",
shiny::tabPanel(title=shiny::icon("star"),value = "start",
shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),
tags$i("Load a dataset to get started!"),
br(),
icon("caret-down", "fa-3x"),
br(),
icon("box-open","fa-5x"),
shiny::br(),shiny::br(),shiny::br(),
shiny::br(),shiny::br()),
shiny::tabPanel(value="switch",
title=shinyBS::tipify(shiny::icon("exchange"),
title = "switch to different variable and/or subset based on variable",
trigger = "hover",options=list(container="body"))
, shiny::h2("Current experiment:"),
shiny::div(
shiny::div(style="display: inline-block;vertical-align:top;",shiny::uiOutput("curr_name")),
style="background-color:white;
width:100%;
margin: 0 auto;
border-top: 1px solid #DFDCDC;
border-bottom: 1px solid #DFDCDC;")
,shiny::hr()
,shiny::h2("Change variable of interest")
,shiny::selectizeInput("stats_type",
label = "Normal, two-factor or time series?",
choices = list("one factor" = "1f",
"two factors" = "2f",
"time series" = "t",
"time series + one factor" = "t1f"),
selected = "1f",width = "80%")
,fluidRow(align="center",shiny::uiOutput("stats_picker"))
,shiny::conditionalPanel("input.stats_type == '1f'",
shiny::checkboxInput("paired",
"Matched samples only?",
value = F))
,shiny::conditionalPanel("input.stats_type == 't' || input.stats_type == 't1f'",
shiny::selectizeInput("time_var",
label="Time series variable:",
choices = c(" "),width = "80%"))
,shinyWidgets::actionBttn(
inputId = "change_cls",
label = "do stats on selected",
style = "bordered",
icon = icon("magic"),
size = "sm"
)
),
shiny::tabPanel(value="subset",
title=shinyBS::tipify(shiny::icon("filter"),
title = "Subset based on variable or m/z(s)",
trigger = "hover",options=list(container="body")),
shiny::hr()
,shiny::h2("Subset data")
,helpText("Current sample count:")
,h2(shiny::textOutput("samp_count"))
,helpText("Current m/z count:")
,h2(shiny::textOutput("mz_count"))
,br()
,shiny::selectizeInput("subset_var", label="Subset data based on:", choices = c(" "),width = "80%")
,shinyWidgets::pickerInput(
inputId = "subset_group",
label = "Group(s) in subset:",
choices = c(" "),
choicesOpt = list(
subtext = c(" ")
),multiple = T)
,shinyWidgets::actionBttn(
inputId = "change_subset",
label = "click to subset by metadata",
style = "bordered",
icon = icon("filter"),
size = "sm"
),br(),br()
# ,shinyWidgets::pickerInput(
# inputId = "subset_mzs",
# label = "Subset by m/z(s):",
# choices = c("M/z with prematches"="prematched"),
# choicesOpt = list(
# subtext = c(" ")
# )),
# shiny::conditionalPanel("input.subset_mzs == 'prematched'",
# shiny::helpText("Only use matches with main isotopes??"),
# shinyWidgets::switchInput(
# inputId = "subset_mz_iso",
# size = "mini",
# onLabel = "Yes",
# offLabel = "No",
# value = TRUE
# )
# ),
# shinyWidgets::actionBttn(
# inputId = "change_subset_mz",
# label = "click to subset by m/z",
# style = "bordered",
# icon = icon("filter"),
# size = "sm"
# ),
# br(),br()
,shinyWidgets::pickerInput(
inputId = "storage_choice",
label = "Load existing meta-dataset:",
choices = c(" "),
choicesOpt = list(
subtext = c(" ")
))
,span(shinyWidgets::actionBttn(
inputId = "load_storage",
label = "load",
style = "bordered",
icon = icon("folder-open"),
size = "sm",
color = "success"
),
shinyWidgets::actionBttn(
inputId = "remove_storage",
label = "delete",
style = "bordered",
icon = icon("eraser"),
size = "sm",
color = "warning"
))
,br(),br()
,helpText("Reset to non-subsetted or paired dataset")
,shinyWidgets::actionBttn(
inputId = "reset_subset",
label = "click to un-subset data",
style = "bordered",
icon = icon("undo"),
size = "sm"
)
),
shiny::tabPanel(value="search",title=shinyBS::tipify(shiny::icon("search"),
title = "search m/z > compound or compound > mz",
trigger = "hover",options=list(container="body")),
shiny::br(),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Options"),
value="search_panel",
shiny::tabsetPanel(id="tab_iden_1", selected = "pick_databases",
# forward searching
shiny::tabPanel(title = shiny::icon("database"),
#title="DBs",
value = "pick_databases",
shiny::uiOutput("db_search_select"),
br(),
shiny::div(id = "curly-brace", shiny::div(id = "left", class = "brace"),
shiny::div(id = "right", class = "brace")),
br(),br(),
shinyWidgets::circleButton("select_db_all",
icon = shiny::icon("shopping-cart"),
size = "default") # shiny::icon("fingerprint"), size = "sm")
),
shiny::tabPanel(title = icon("medal"),
shiny::fluidRow(
shiny::helpText("Only consider highly correlated m/z values?"),
shinyWidgets::switchInput(
inputId = "score_use_corr",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::conditionalPanel("input.score_use_corr == true",
shiny::selectizeInput(width = "80%","score_corr_method",
"Which correlation method used?",
selected="pearson",
choices=list("pearson",
"spearman",
"kendall"
)),
shiny::sliderInput("score_corr_min",
label = "Min required correlation: ",
min = 0, max = 1,
value = 0.9,
step = 0.05)
)
),
shiny::tabsetPanel(
shiny::tabPanel(title=icon("percentage"),#title="isoScore",
shiny::fluidRow(align="center",
shiny::br(),
shiny::h2("isoMatcher"),
shiny::h3("Score matches by isotope pattern"),
shiny::helpText("Per match, investigates if other same-formula isotopes are present."),
shiny::helpText("Score pattern intensity simularity? (if not, only check for isotope presence)"),
shinyWidgets::switchInput(
inputId = "iso_use_int",
size = "mini",
onLabel = "Yes",
offLabel = "No",
value = TRUE
),
shiny::conditionalPanel("input.iso_use_int == true",
shiny::selectizeInput(width = "80%","iso_score_method",
"Which method used to score compounds of same weight?",
selected="mscore",
choices=list("M-score" = "mscore"
#"Chi-square" = "chisq",
#"Mean absolute percentage error" = "mape",
#"SIRIUS" = "sirius",
#"Network-based" = "network"
)),
shiny::sliderInput("int_prec",
label = "Intensity error margin",
min = 1, max = 100,
value = 2, post = "%")
),
shiny::uiOutput("iso_rt_ui"),
shinyWidgets::circleButton("score_iso", icon = shiny::icon("medal"), size = "sm"))
),
shiny::tabPanel(title=shiny::icon("clock"),
shiny::fluidRow(align="center",
shiny::br(),
shiny::h2("addMatcher"),
shiny::h3("Score matches by fellow adducts"),
shiny::helpText("Per match, investigates if other main isotope adducts are present."),
shinyWidgets::pickerInput(inputId = "score_adducts",
choices = adducts$Name,
label = "Adducts to look for:",
selected = c("[M+H]1+", "[M+Na]1+", "[M+2H]2+", "[M+K]1+"),
multiple = T,
options = list(
`actions-box` = TRUE)),
shiny::uiOutput("score_adducts_cats"),
shiny::uiOutput("add_rt_ui"),
shinyWidgets::circleButton("score_add",
icon = shiny::icon("medal"),
size = "sm")
))
)
),
shiny::tabPanel(title=shiny::icon("cloud"),#title="wordcloud",
tabsetPanel(id="wordclouds", selected = "settings",
tabPanel(title="settings",
shiny::br(),
shinyWidgets::switchInput(
inputId = "wordcloud_manual",value = TRUE,
onLabel = "own word",#<i class=\"fas fa-cloud\"></i>",
offLabel = "from matches"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
shiny::tabPanel("input.wordcloud_manual == true",
helpText("Type a metabolite below and search PubMed to find documents that contain that word in the text."),
textInput("wordcloud_searchTerm", label = h3("Enter your search terms"), placeholder = "enter your search terms"),
helpText("You can specify the start and end years of your search, use the format YYYY"),
sliderInput(inputId = "wordcloud_dateRange", label = "Date range input:",min = 2000, max = 2025, value = c(2010, 2020), sep = ""),
sliderInput("wordcloud_absFreq", "Amount of abstracts to use:", min = 1, max = 4000, value = 500)
),
actionButton("do_wordcloud", "Plot")
),
tabPanel(title = "filters",
helpText("Type a search term: a word filter will be created with the resulting top words."),
textInput("wordcloud_filterTerm", label = h3("Enter your search terms"), placeholder = "enter your search terms"),
helpText("You can specify the start and end years of your search, use the format YYYY"),
sliderInput(inputId = "wordcloud_filterDateRange", label = "Date range input:",min = 2000, max = 2025,value = c(2010, 2020), sep = ""),
sliderInput("wordcloud_filterAbsFreq", "Amount of abstracts to use:", min = 10, max = 500000, value = 5000),
sliderInput("wordcloud_filterTopN", "Top words used for filter:", min = 1, max = 5000, value = 500),
actionButton("wordcloud_make_filter", "Go! :)")
),
tabPanel(title = "plot",
shiny::conditionalPanel('input.wordbar == true',
wordcloud2::wordcloud2Output(outputId = "wordcloud"),
tags$script(HTML(
"$(document).on('click', '#canvas', function() {",
'word = document.getElementById("wcSpan").innerHTML;',
"Shiny.onInputChange('wordcloud_selected_word', word);",
"});"
))
),
conditionalPanel('input.wordbar == false',
shiny::uiOutput("wordbar_wrap")
),
shinyWidgets::switchInput(
inputId = "wordbar",value = TRUE,
onLabel = "cloud",#<i class=\"fas fa-cloud\"></i>",
offLabel = "barchart"# "<div class=\"fa-flip-vertical\"><i class=\"fas fa-chart-bar fa-rotate-90\"></i></div>"
),
br(),
shiny::sliderInput("wordcloud_topWords", "Top words used for plot:", min = 1, max = 10000, value = 100),
shiny::selectizeInput("wordcloud_filter",
"Filter",
choices = c("stopwords"),
selected="stopwords",
multiple = T),
shiny::wellPanel(id = "def",style = "overflow-y:scroll; max-height: 400px; font-size: 80%",
helpText("Click a word to see abstracts!"),
shiny::uiOutput("wordcloud_abstracts")
)
)
)
)
))),
br(),
shiny::uiOutput("manual_search"),
br(),
div(shiny::fluidRow(align="center",
div(
br(),br(),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shinyWidgets::pickerInput(
inputId = "curr_mz",
label = div(icon("search"), style="font-size: xx-large;margin-top: -30px;color: black;-webkit-text-fill-color: white;-webkit-text-stroke-width: 1.5px;-webkit-text-stroke-color: #DFDCDC"),
choices = "fa-cat",
choicesOpt = list(
subtext = "",
style='text-align:center;'),
options = list(
`live-search` = TRUE,
size = 10)
),class = "mzpicker"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="display: flex;"),
div(shiny::icon("paw", "fa-xs fa-rotate-90"), style="margin-top: 20px; display: flex;"),
br(),
style = "align-items: center; display: inline-flex;"),
),
shinyWidgets::prettyToggle(
status_off = "default",
status_on = "warning",
bigger = T,
animation = "pulse",
inputId = "star_mz",
label_on = "",
label_off = "",
outline = TRUE,
plain = TRUE,
value = FALSE,
icon_on = icon("star"),
icon_off = htmltools::browsable(tags$i(class = "far fa-star"))
),
style = "border-top: 1px solid #DFDCDC; border-bottom: 1px solid #DFDCDC; margin-left: -15px; margin-right: -15px; background-color:white;"),
br(),
shiny::tabsetPanel(id = "tab_search", shiny::tabPanel(title = shinyBS::tipify(shiny::icon("paw"),
"mz <> molecule matches"),
shinyBS::bsCollapse(shinyBS::bsCollapsePanel(title=shiny::h2("Compound info"),
value="panel2",
shiny::tabsetPanel(id="tab_iden_3",
shiny::tabPanel(title=shiny::icon("atlas"),
wellPanel(id = "def",style = "overflow-y:scroll; max-height: 200px",
shiny::uiOutput("desc_ui")
)
),shiny::tabPanel(title=shiny::icon("atom"),
br(),
shiny::imageOutput("empty4",width="100%",height="1px"),
shiny::uiOutput("curr_formula"),
shiny::plotOutput("curr_struct",inline = T)
)
))),
shiny::tabsetPanel(id="tab_iden_2",
# forward searching
shiny::tabPanel(title="mz > molecule",value = "mzmol",
br(),
shiny::tags$i("Found matches for this m/z value:"),
br(),
shinyWidgets::searchInput(
inputId = "match_search_query",
label = "Search compound descriptions",
placeholder = "",
btnSearch = icon("search"),
btnReset = icon("remove"),
width = "100%"
),
shiny::fluidRow(align="left",
shiny::div(DT::dataTableOutput('match_tab'),
style='font-size:80%;'))
),
# reverse searching
shiny::tabPanel(title="molecule > mz",value = "molmz",
br(),
shiny::tags$i("Press the below button to browse compounds of the selected databases."),br(),
shiny::actionButton("browse_db", "Browse", icon=shiny::icon("eye")),
br(),
shiny::div(DT::dataTableOutput('browse_tab'),style='font-size:80%'),
br(),
shiny::tags$i("M/z values matching adducts or isotopes of this compound:"),br(),
shiny::div(DT::dataTableOutput('hits_tab'),style='font-size:80%')
)),
shiny::fluidRow(
shiny::div(shiny::helpText("Show heavy C, N, O count if available?"),
style='font-size:80%;'),
shinyWidgets::switchInput(
inputId = "show_iso_labels",
size = "mini",
onLabel = "show",
offLabel = "hide",
value = FALSE
)),
br(),
shiny::helpText("Current match filtering:"),
shiny::fluidRow(align="center",
shiny::imageOutput("empty",width="100%",height="1px"),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("plus-circle")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_add"),style='font-size:60%;padding:2px')),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("percentage")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_iso"),style='font-size:60%;padding:2px')),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::icon("database")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::div(verbatimTextOutput("curr_db"),style='font-size:60%;padding:2px'))
),
shiny::helpText("Undo match filtering"),
shinyWidgets::circleButton("undo_match_filt", icon = shiny::icon("undo-alt")),
br()
),
shiny::tabPanel(title=shinyBS::tipify(shiny::icon("filter"),
title = "filter matches on adduct, isotope or database"),
value="match_filters_tab",
shinyWidgets::verticalTabsetPanel(id = "match_filters",
contentWidth = 10,
menuSide = "right",
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("plus","fa-2x"),value = "pie_add",
plotly::plotlyOutput("match_pie_add"),
shiny::uiOutput("filter_adducts_cats")
),
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("percentage","fa-2x"),value = "pie_iso",
plotly::plotlyOutput("match_pie_iso")
),
shinyWidgets::verticalTabPanel(box_height = "80px",
title = NULL, icon = icon("database","fa-2x"),value = "pie_db",
plotly::plotlyOutput("match_pie_db")
)
),br()
))),
# this tab is used to select user plot theme and user colours (discrete and continuous)
shiny::tabPanel(value="plot_aes", title=shinyBS::tipify(shiny::icon("paint-brush"),
title="change plot style and colours",
trigger = "hover",options=list(container="body")),
shiny::h2("Plot style"),br(),
helpText("Click to reload plot:"),
shinyWidgets::circleButton("reload_plots",
icon = shiny::icon("paint-brush")),
br(),
helpText("Use ggplot or plotly for plots? (ggplot -> faster, but no interactivity)"),
shinyWidgets::switchInput(
inputId = "ggplotly",
onLabel = "plotly",
offLabel = "ggplot",
offStatus = "warning",
onStatus = "info",
value = T
),
helpText("Export plots as .png or .svg?"),
shinyWidgets::switchInput(
inputId = "plotsvg",
onLabel = "svg",
offLabel = "png",
offStatus = "info",
onStatus = "warning",
value = T
),
shiny::h2("Legend"),br(),
shinyWidgets::switchInput(
inputId = "legend",
size = "mini",
onLabel = "show",
offLabel = "hide",
value = FALSE
),
shiny::h2("M/z labels"),
shiny::tags$i("only ggplot mode"),
shinyWidgets::switchInput("plot_mzlabels", value = T, onLabel = "show", offLabel="hide", size = "small"),
shiny::numericInput("ggplot_font_size",label = "Plot font base size:",value = 15),
plotly::plotlyOutput("ggplot_font_size_example"),
shiny::selectizeInput("ggplot_sum_style", multiple=T, label = "Style(s)", choices = list("Box" = "box",
"Violin" = "violin",
"Beeswarm" = "beeswarm",
"Scatterplot" = "scatter",
"Sina" = "sina"
),
selected = c("beeswarm"),width = "80%"),
shiny::selectizeInput("ggplot_sum_stats", label = "Stats shown", choices = list("median", "mean", "none"),width = "80%"),
shiny::h2("Shape")
,shiny::selectizeInput("shape_var", label="Marker shape based on:", choices = c(" "),width = "80%")
,shiny::h2("Color")
,shiny::selectizeInput("fill_var", label="Marker fill color based on:", choices = c(" "),width = "80%")
,shiny::selectizeInput("col_var", label="Marker outline color based on:", choices = c(" "),width = "80%")
,shiny::h2("Hover text")
,shiny::selectizeInput("txt_var", label="Marker hover text based on:", choices = c(" "),width = "80%"),
# input$plot_mzlabels
shiny::h2("Plot theme"),
shiny::selectizeInput("ggplot_theme", label = "Theme", choices = list("Grid, white bg" = "bw",
"No grid, white bg" = "classic",
"Grid, gray bg" = "gray",
"Minimal" = "min",
"Grid, black bg" = "dark",
"Grid, white bg, gray axes" = "light",
"Line drawing" = "line"),
selected = "min",width = "80%"),
plotly::plotlyOutput("ggplot_theme_example",inline = F),
shiny::h2("Continuous data"),
# the below options need to match with the corresponding function storage in 'global'. if you want to add more it'll go here!
shiny::selectizeInput("color_ramp", label = "Color scheme", choices = list("RAINBOW!" = "rb",
"Yellow - blue" = "y2b",
"Matlab 1" = "ml1",
"Matlab 2 " = "ml2",
"Magenta - Green" = "m2g",
"Cyan - yellow" = "c2y",
"Blue - yellow" = "b2y",
"Green - red" = "g2r",
"Blue - green" = "b2g",
"Blue - red" = "b2r",
"Blue - pink (pastel)" = "b2p",
"Blue - green - yellow" = "bgy",
"Green - yellow - white" = "gyw",
"Red - yellow - white" = "ryw",
"Grayscale" = "bw",
"Blues (brew)" = "Blues",
"Blue - green (brew)" = "BuGn",
"Blue - purple (brew)" = "BuPu",
"Green - blue (brew)" = "GnBu",
"Greens (brew)" = "Greens",
"Grayscale (brew)" = "Greys",
"Oranges (brew)" = "Oranges",
"Orange - red (brew)" = "OrRd",
"Purple - blue (brew)" = "PuBu",
"Purple - blue - green (brew)" = "PuBuGn",
"Purple - red (brew)" = "PuRd",
"Purples (brew)" = "Purples",
"Red - purple (brew)" = "RdPu",
"Reds (brew)" = "Reds",
"Yellow - green (brew)" = "YlGn",
"Yellow - green - blue (brew)" = "YlGnBu",
"Yellow - orange - brown (brew)" = "YlOrBr",
"Yellow - orange - red (brew)" = "YlOrRd",
"BrBG", "PiYG", "PRGn", "PuOr", "RdBu", #TODO: add descriptions (or remove all?)
"RdGy", "RdYlBu", "RdYlGn", "Spectral",
"Accent", "Dark2", "Paired", "Pastel1",
"Pastel2", "Set1", "Set2", "Set3"),selected = "rainbow",width = "80%"
),
# preview plot
plotly::plotlyOutput("ramp_plot"),
shiny::h2("Discrete data"),
shiny::uiOutput("colorPickers")
),
shiny::tabPanel(value="metadata",
title = shinyBS::tipify(shiny::icon("plus"),
trigger = "hover",
title = "upload new metadata file",options=list(container="body")),
br(),br(),
shiny::h2("New metadata"),
shiny::helpText("If you want to update your metadata, please use the below upload screen!
Any samples missing in your uploaded csv will be labeled as 'unknown' for new metadata columns."),
shiny::fileInput(inputId = "metadata_new", "Select metadata", buttonLabel="Browse"),
#shinyFiles::shinyFilesButton('metadata_new', 'upload', 'Select metadata', FALSE),
shinyWidgets::circleButton("metadata_new_add", icon = shiny::icon("arrow-right"))
)))))
))),
# # report tab
# shiny::tabPanel("report",
# icon = shiny::icon("file-invoice", class = "outlined"),
# value="report",
# shiny::fluidRow(align="center", shiny::h2("Report")),
# shiny::fluidRow(
# shiny::column(width=5, align="center",
# shiny::div(DT::dataTableOutput('report_unselected',
# width="100%"))
# ),
# shiny::column(width = 2, align="center",
# shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),shiny::br(),
# shinyWidgets::circleButton("report_add", icon=shiny::icon("arrow-right")),
# shiny::br(),
# shinyWidgets::circleButton("report_remove", icon=shiny::icon("arrow-left"))
# ),
# shiny::column(width=5, align="center",
# shiny::div(DT::dataTableOutput('report_selected',
# width="100%"))
# )
# ),shiny::br(),
# shiny::fluidRow(align="center",
# shinyWidgets::circleButton("make_report",
# icon=shiny::icon("file-invoice"),
# size="lg")
# )
# ),
# this tab is used to change general settings.
shiny::tabPanel("settings", icon = shiny::icon("cog",class = "outlined"), value="options",
shiny::tabsetPanel(id="tab_settings",selected = "Global",
shiny::tabPanel("Global", icon=shiny::icon("box-open"),
# MetaboShiny::switchButton(inputId = "db_only", label = "Run in database-only mode?",
# value = F,
# col = "BW", type = "YN")
shiny::fluidRow(align="center",
# work folder
shinyFiles::shinyDirButton("get_work_dir",label = "Change projects folder",title = "Pick projects directory"),
shiny::textOutput("curr_exp_dir"),
# db folder
shinyFiles::shinyDirButton("get_db_dir",label = "Change database folder", title = "Pick database directory"),
shiny::textOutput("curr_db_dir"),br(),
shiny::sliderInput("ncores", "How many cores can MetShi use?",
value = 1, min = 1,
max = 2,step = 1,post = " cores"),
shiny::uiOutput("ncore_ui"),
shiny::br(),
shiny::numericInput("seed", "Which seed do you want to use for randomization?",value = 1337),
shiny::actionButton("set_seed",label = "apply"),
shiny::br(),
shiny::helpText("How to handle samples with missing metadata? (re-checked each subset/switch step)?"),
shinyWidgets::switchInput(
inputId = "omit_unknown",
onLabel = "omit",
offLabel = "keep",
offStatus = "success",
onStatus = "danger",
value = T
),
shiny::br(),
shiny::selectizeInput("beep",
label = "Noise to make after task is done:",
choices = list(
"none",
"ping",
"coin",
"fanfare",
"complete",
"treasure",
"ready",
"shotgun",
"mario",
"wilhelm",
"facebook",
"sword"
), selected = 1)
)
),
shiny::tabPanel("Project", icon=shiny::icon("gift"),
#shiny::textInput(inputId="proj_name", label="Project name", value = ''),
shiny::fluidRow(align="center",
shiny::selectizeInput(inputId="proj_name",
label="Project name",
choices=c("..."), # existing projects in user folder (generated in 'global')
selected = "...",
options=list(create = TRUE)), # let users add new names
shiny::actionButton("set_proj_name", label="Apply"),
shiny::hr(),
shiny::helpText("Clone project (to skip file input w/ different normalization)"),
shiny::textInput(inputId = "proj_clone_name", label = "Cloned project name:"),
shiny::actionButton("clone_proj", label = "Clone")
)
),
shiny::tabPanel("Search", icon = shiny::icon("paw"),
br(),
shiny::fluidRow(align="center",
shinyWidgets::materialSwitch(
inputId = "autocopy",
label = "Copy compound info to clipboard?",
value = TRUE,
status = "success"
),
shiny::conditionalPanel("input.autocopy == true",
shinyWidgets::radioGroupButtons(
inputId = "matchAutocopy",
label = "What info will you copy?",
choices = c("SMILES",
"name",
"formula"),
checkIcon = list(
yes = icon("ok",
lib = "glyphicon"))
)
))),
# change list of adducts used, or add your own
# TODO: fix, i think this is currently non-functional
shiny::tabPanel("Adducts", icon=shiny::icon("plus-square"),
shiny::tabsetPanel(
shiny::tabPanel("Current adducts",
shiny::tabsetPanel(
shiny::tabPanel("Definitions",
shiny::fluidRow(align="center",shiny::h3("Current adduct table:")),
rhandsontable::rHandsontableOutput("adduct_tab",
width='100%',
height='70%'),
shiny::fluidRow(align="center",shiny::fileInput(inputId = "add_tab",
"Import adduct table",
multiple = F,
accept = c(".RData", ".csv")),
shiny::div(style="display: inline-block;vertical-align:top;",shiny::actionButton("import_adducts", "Import definitions"))
)
),
shiny::tabPanel("Rules",
shiny::fluidRow(align="center", shiny::h3("Current adduct rules:")),
rhandsontable::rHandsontableOutput("adduct_rules_tab",
width='100%',
height='70%'),
shiny::fileInput(inputId = "add_rule_tab",
"Import adduct rule table",
multiple = F,
accept = c(".RData", ".csv")),
shiny::fluidRow(align="center",
shiny::div(style="display: inline-block;vertical-align:top;",shiny::actionButton("import_adduct_rules", "Import rules"))
)
)
),
shiny::fluidRow(align="center",
shiny::actionButton("save_adducts","Save changes"),
shiny::hr()
)
)
)
),
shiny::tabPanel("Formula prediction & lookup",
icon=shiny::icon("searchengin"),
shiny::fluidRow(align="center",
br(),
shiny::passwordInput("apikey",
label = "If you want to use ChemSpider, please register on their website and enter your API key below.",
value = ""),
shiny::div(style="display: inline-block;vertical-align:top;",shinyWidgets::circleButton("set_api", icon = icon("save"))),shiny::div(style="display: inline-block;vertical-align:top;",shiny::textOutput("api_set")),
selectizeInput("predict_rules",
label = "Use which chemical formula rules?",
choices = c("senior", "lewis", "hc", "chnops", "nops"),
multiple = T,
selected = c()),
selectizeInput("predict_elements", label = "Consider which atoms? (including adducts!)",
choices = c("C","H","N","O","P","S"), selected = c("C","H","N","O","P","S"), multiple = T),
MetaboShiny::switchButton(inputId = "predict_details",
label = "Get detailed PubChem matches? (SLOW, be warned!)",
col = "BW", type = "YN", value = F),
MetaboShiny::switchButton(inputId = "predict_structure_check",
label = "Uniformize ChemSpider/PubChem found structures?",
col = "BW", type = "YN", value = T),
MetaboShiny::switchButton(inputId = "predict_adduct_rules",
label = "Filter ChemSpider/PubChem hits with available structures using your adduct rules?",
col = "BW", type = "YN", value = F))),
# change toolbar colour, text font and size
shiny::tabPanel("Aesthetic", icon=shiny::icon("child"),
shiny::fluidRow(align="center",
shiny::h3("Change app settings"),
shiny::hr(),
shiny::h2("Navigation bar colours"),
colourpicker::colourInput(inputId = "bar.col.1",
label = paste("Inactive background"),
#value = opts$col1,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.2",
label = paste("Active background"),
#value = opts$col2,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.3",
label = paste("Inactive tab text"),
#value = opts$col3,
allowTransparent = FALSE),
colourpicker::colourInput(inputId = "bar.col.4",
label = paste("Active tab text"),
#value = opts$col4,
allowTransparent = FALSE),
shiny::br(),
shiny::a(shiny::h2("Fonts (Google fonts)"), href = "https://fonts.google.com/", target="_blank"),
shiny::textInput(inputId="font.1", label="h1", value = "Leckerli One"),
shiny::textInput(inputId="font.2", label="h2", value = "Leckerli One"),
shiny::textInput(inputId="font.3", label="h3", value = "Open Sans"),
shiny::textInput(inputId="font.4", label="body", value = "Open Sans"),
shiny::br(), # TODO: font size modifier slider
shiny::h2("Font size"),
shiny::sliderInput("size.1", label="h1", value=30,min = 5, max=50),
shiny::sliderInput("size.2", label="h2", value=20,min = 5, max=50),
shiny::sliderInput("size.3", label="h3", value=13,min = 5, max=50),
shiny::sliderInput("size.4", label="body", value=10,min = 5, max=50),
shiny::hr(),
shiny::actionButton("change_css", "Save settings (restart to apply)")
)
)
)
),
shiny::tabPanel("help", icon=shiny::icon("question",class="outlined"),
shiny::fluidRow(align = "center",style="li { display:inline-table; }",
shiny::uiOutput("help"))),
# prompt user on opening the quit tab.
# TODO: add 'save project?' dialog
shiny::div(class="scallop-down"),
shiny::div(class="cursorHolder"),
shiny::div(class="line"),
footer=
shiny::div(class = "footer",
shiny::fluidRow(align="center",
shiny::span(shiny::tags$i(icon("map-marker"),
shiny::textOutput("proj_name",inline = T),
style="vertical-align: middle;")),
shiny::actionButton("load_mset", label="load",
icon = shiny::icon("folder-open")),
shiny::actionButton("save_mset", label="save",
icon = shiny::icon("save")),
shiny::actionButton("debug_metshi", label="send to R",
icon = shiny::icon("r-project")),
shiny::actionButton("quit_metshi", label="quit", icon = shiny::icon("eraser")),
shiny::span(shiny::tags$i(icon("stopwatch"), shiny::textOutput("last_saved",inline = T), style="vertical-align: middle;")),
shiny::span(shiny::uiOutput("has_unsaved_changes",inline = T), style="margin-left: 10px;")
)
)
), style="margin-bottom:100px;")
)
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