R/module_help.R

In ComputationalProteomics/OmicLoupe: OmicLoupe: Taking a closer look at omics

setup_help_ui <- function(id) {
    ns <- shiny::NS(id)
    tabPanel(
        id,
        fluidPage(
            fluidRow(
                tabsetPanel(
                    id = ns("help_panels"),
                    type = "tabs",
                    tabPanel(
                        "Setup page", 
                        h3("Video links here too"),
                        htmlOutput(ns("setup_image_text")),
                        plotOutput(ns("setup_image"), height = 800)
                    ),
                    tabPanel(
                        "Statistics page",
                        htmlOutput(ns("plotly1_image_text")),
                        plotOutput(ns("plotly1_image"), height = 1050)
                    ),
                    tabPanel(
                        "Statistics page 2",
                        htmlOutput(ns("plotly2_image_text")),
                        plotOutput(ns("plotly2_image"), height = 1050)
                    ),
                    tabPanel(
                        "PCA page",
                        htmlOutput(ns("pca_image_text")),
                        plotOutput(ns("pca_image"), height=1000)
                    ),
                    tabPanel(
                        "Input data formats",
                        htmlOutput(ns("input_data_text"))
                    )
                )
            )
        )
    )
}

module_help_server <- function(input, output, session, module_name) {

    output$setup_image <- renderImage({
        filename <- normalizePath(file.path("./doc", "setup_screen.png"))
        list(src = filename)
    }, deleteFile = FALSE)
    
    output$setup_image_text <- renderUI({
        HTML(parse_vector_to_bullets(c(
            "Select dataset 1 or 2",
            "Upload tab delimited data file containing sample columns and optionally annotation",
            "Column names will automatically appear here on upload",
            "Optional design matrix with annotation for each sample",
            "What column contains sample names - should be exact match to what is found in the data file",
            "Select or deselect samples manually by marking in the left/right panels and moving with arrow buttons",
            "Select or deselect statistics columns manually",
            "Detect sample columns and statistics columns automatically based on patterns matching the pattern 'pattern.P.Value$'. Sample columns are retrieved from the design matrix.",
            "Information about mapping between datasets",
            "Select sample columns",
            "Selected statistics columns",
            "The statistic columns are expected to follow the pattern 'base.P.Value', 'base.adj.P.Val', 'base.logFC' and 'base.AvgExpr'. This displays all patterns matching this.",
            "Column among data columns containing unique identifier which can be used to map across datasets"
        )))
    })
    
    output$plotly1_image <- renderImage({
        filename <- normalizePath(file.path("./doc", "plotly_screen1.png"))
        list(src = filename)
    }, deleteFile = FALSE)
    
    output$plotly1_image_text <- renderUI({
        HTML(parse_vector_to_bullets(c(
            "First",
            "Second"
        )))
    })
    
    output$plotly2_image <- renderImage({
        filename <- normalizePath(file.path("./doc", "plotly_screen2.png"))
        list(src = filename)
    }, deleteFile = FALSE)
    
    output$plotly2_image_text <- renderUI({
        HTML(parse_vector_to_bullets(c(
            "First",
            "Second"
        )))
    })
    
    output$pca_image <- renderImage({
        filename <- normalizePath(file.path("./doc", "PCA_screen.png"))
        list(src = filename)
    }, deleteFile = FALSE)
    
    output$pca_image_text <- renderUI({
        HTML(parse_vector_to_bullets(c(
            "First",
            "Second"
        )))
    })
    
    output$input_data_text <- renderUI({
        HTML(parse_vector_to_bullets(c(
            "Need to specify requirements on input files",
            "1. Data file, containing statistical columns and specify feature column (and optional annotation column)",
            "2. Design file, containing experimental condition with one column mapping to the data file, and other columns could be used for visualization colorings",
            "Column identification logic",
            "Data loading",
            "Using matched samples"
        )))
    })
    
    parse_vector_to_bullets <- function(vect, number=TRUE) {
        html_string <- paste0(
            "<li>",
            paste(vect, collapse="</li><li>"),
            "</li>"
        )
        
        if (!number) {
            list_style <- "ul"
        }
        else {
            list_style <- "ol"
        }
        
        sprintf("<%s>%s</%s>", list_style, html_string, list_style)
    }
    
    
    # output$help_setup <- renderText({
    #     "There are three separate panels."
    # })
    # 
    # output$help_plotly <- renderText({
    #     "Plotly text"
    # })
    # 
    # output$help_pca <- renderText({
    #     "PCA text"
    # })

}