inst/app/featureProcUI.R

In jordirofes/OmniOmics: Analysis of metabolomics (LC-MS) and transcriptomics (Microarray) data

featureProcUI <- function(id){
    ns <- NS(id)
    tabsetPanel(
        tabPanel(title = "Feature Proc",
            fluidPage(
                fluidRow(
                    column(width = 4,
                        selectInput(inputId = ns("object"), label = "Select an object to process:",
                                    choices = "")
                    ),
                    column(width = 4,
                        selectInput(inputId = ns("omic"), label = "Select an omic:",
                                    choices = c("Metabolomics", "Transcriptomics", "Both"))
                    ),
                    column(width = 4,
                        actionButton(inputId = ns("featProcBut"), label = "Process Features:")
                    )
                ),
                conditionalPanel("input.omic == 'Metabolomics'",
                    fluidRow(
                        column(width = 4,
                            switchInput(ns("ism0Filt"), label = "Filter non M0 features"),
                            switchInput(ns("annoFilt"), label = "Filter non annotated features"),
                            switchInput(inputId = ns("prePro"), label = "Pre-processing options"),

                        ),
                        column(width = 4,
                            switchInput(inputId = ns("blankFilt"), label = "Blank Filter"),
                            switchInput(inputId = ns("cvFilt"), label = "Filter by variation coefficient"),
                            switchInput(inputId = ns("naFilt"), label = "Filter by NA ratio"),
                        ),
                        column(width = 4,
                            switchInput(inputId = ns("metVarFilt"), label = "Variance Filter"),
                            switchInput(inputId = ns("intFilt"), label = "Intensity Filter"),
                            switchInput(inputId = ns("sampleFilt"), label = "Sample Filter")
                        )
                    ),
                    fluidRow(
                        column(width = 4,
                            selectInput(inputId = ns("groupVar"), label = "QC/Sample/Blank variable:",
                                        choices = ""),
                            selectInput(inputId = ns("blankname"), label = "Select a blank name", choices = ""),
                            selectInput(inputId = ns("qcname"), label = "Select the QC name", choices = ""),
                        ),
                        column(width = 4,
                            conditionalPanel("input.blankFilt",
                                numericInput(inputId = ns("blankRatio"), label = "Select a fold-change between sample and blank:",
                                            value = 1, min = 0, max = 100, step = 0.1)

                            , ns = ns),
                            conditionalPanel("input.cvFilt",
                                numericInput(inputId = ns("maxRDS"),
                                            label = "Select a maximum QC RDS % threshold::",
                                            value = 20, min = 0, max = 100, step = 1)
                            , ns = ns),
                            conditionalPanel("input.naFilt",
                                numericInput(inputId = ns("nathr"), label = "NA ratio threhshold",
                                            value = 0.4, min = 0, max = 1, step = 0.01),
                                selectInput(inputId = ns("naMethod"), label = "Select a NA ratio method:",
                                            choices = c("WithinQC" = "QC", "WithinSampleClass" = "within",
                                                        "AcrossAllSamples" = "across"))
                            , ns = ns),
                            conditionalPanel("input.prePro",
                                selectInput(inputId = ns("preProFuns"), label = "",
                                            choices = c("mvImp", "pqn", "glog", "sum", "blankfill"), multiple = TRUE),
                                selectInput(inputId = ns("mvImpMeth"), label = "Multivariate imputation method:",
                                            choices = c("knn", "rf")), ns = ns)
                        ),
                        column(width = 4,
                            conditionalPanel("input.metVarFilt",
                                selectInput(inputId = ns("varfun"), label = "Select a variance function:",
                                            choices = c("IQR", "CV", "SD")),
                                switchInput(inputId = ns("quant"), label = "Filter by quantile"),
                                numericInput(inputId = ns("varthr"), label = "Select variance threshold",
                                            value = 0.6, min = 0, max = 1000, step = 0.01),
                                selectInput(inputId = ns("groupName"),
                                            label = "Select a specific group to compute the variances (samples for example):",
                                            choices = "")
                            , ns = ns),
                            conditionalPanel("input.intFilt",
                                numericInput(inputId = ns("intthr"), label = "Select a intensity threhshold (absolute):",
                                            min = 0, value = 100, max = 10000000, step = 1)
                            , ns = ns),
                            conditionalPanel("input.sampleFilt",
                                numericInput(inputId = ns("maxNA"), label = "Select a missing value threshold:",
                                            min = 0, max = 1, value = 0.4, step = 0.01),
                                selectInput(inputId = ns("filtName"),
                                            label = "Select an optional group variable name to filter all it's samples:",
                                            choices = "")
                            , ns = ns)
                        )
                    )
                , ns = ns),
                conditionalPanel("input.omic == 'Transcriptomics'",
                    fluidRow(
                        column(width = 4,
                            switchInput(inputId = ns("entrez"), label = "Remove non entrez genes and duplicated")
                        ),
                        column(width = 4,
                            switchInput(inputId = ns("varfilt"), label = "Variance Filter")
                        )
                    ),
                    fluidRow(
                        conditionalPanel("input.varfilt",
                            column(width = 4,
                                selectInput(inputId = ns("varfun"), label = "Select the variance function to apply:",
                                            choices = c("IQR", "CV", "SD")),
                                numericInput(inputId = ns("quantvar"), label = "Select the quantile to eliminate:",
                                            value = 0.6, min = 0, max = 1, step = 0.01)
                            )
                        ,ns = ns),
                    )
                , ns = ns),
                conditionalPanel("input.omic == 'Both'",
                    fluidRow(
                        column(width = 4,
                            switchInput(inputId = ns("compFilter"), label = "Remove non-significant features")
                        ),
                        column(width = 4,
                            switchInput(inputId = ns("bioFilter"), label = "Filter with biosign model")
                        )
                    ),
                    fluidRow(
                        conditionalPanel("input.compFilter",
                            column(width = 4,
                                selectInput(inputId = ns("compTable"),
                                            label = "Select the comparison table to use for filtering:",
                                            choices = ""),
                                switchInput(inputId = ns("padj"), label = "Adjusted p-value?"),
                                numericInput(inputId = ns("pthr"), label = "P-value threshold",
                                            value = 0.05, min = 0, max = 1, step = 0.01),
                                numericInput(inputId = ns("fcthr"), label = "log2(Fold-Change) threshold",
                                             value = 1, min = 0, max = 100, step = 1)
                            )
                        , ns = ns),
                        conditionalPanel("input.bioFilter",
                            column(width = 4,
                                selectInput(inputId = ns("bioSign"),
                                            label = "Select a biosign model to use for filtering:",
                                            choices = ""),
                                selectInput(inputId = ns("minScore"),
                                            label = "Select the minimum biosign score",
                                            choices = c("S","A", "B","E")),
                                selectInput(inputId = ns("bioSignMod"),
                                            label = "Select which model scores to use:",
                                            multiple = TRUE, choices = c("svm", "random forest", "pls-da"))
                            )
                        ,ns = ns)
                    )
                , ns = ns)
            )
        ),
        tabPanel(title = "Variance Plot",
            fluidPage(
                fluidRow(
                    column(width = 4,
                        selectInput(inputId = ns("object2"), label = "Select an object to process:",
                                    choices = "")
                    ),
                    column(width = 4,
                        selectInput(inputId = ns("varfunction"), label = "Variance function:", choices = c("IQR", "CV", "SD"))
                    )
                ),
                fluidRow(
                    column(width = 12,
                        plotlyOutput(outputId = ns("varplot"))
                    )
                )
            )
        )
    )
}