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| require(shiny) | ||
| require(shiny.gosling) | ||
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| # The variable cistrome_data contains a URL pointing to a dataset | ||
| # in the Cistrome database, which is a multivec data source. | ||
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| # "Multivec" is a term used in genomics to refer to a specific | ||
| # type of data format used for representing and visualizing | ||
| # multi-dimensional numerical data across genomic coordinates. | ||
| # It's commonly used for representing data like ChIP-seq, ATAC-seq, | ||
| # Hi-C, and other genomic experiments where signals or measurements | ||
| # are collected at various genomic positions. | ||
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| # Multivec data is essentially a matrix where rows correspond to | ||
| # different genomic positions or regions, and columns correspond | ||
| # to different samples or experiments. Each entry in the matrix | ||
| # represents a value associated with a specific genomic position | ||
| # and sample. The genomic positions along the rows of the matrix | ||
| # are usually represented as chromosomal coordinates (chromosome | ||
| # name and base pair position). This allows the data to be aligned | ||
| # with the genome, enabling accurate visualization and analysis. | ||
| # There are different tools and file formats that support multivec | ||
| # data, allowing researchers to work with and visualize this type of | ||
| # data. The bigWig and bedGraph formats are commonly used for | ||
| # representing multivec data. Visualization tools and libraries | ||
| # like the UCSC Genome Browser, IGV (Integrative Genomics Viewer), | ||
| # and libraries like "shiny.gosling" can render multivec data visualizations. | ||
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| cistrome_data <- | ||
| "https://server.gosling-lang.org/api/v1/tileset_info/?d=cistrome-multivec" | ||
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| # The add_single_track function is used to create a single track visualization. | ||
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| # The track_data function is used to define the data source for the track. | ||
| # It specifies the URL of the dataset, the type of data ("multivec"), | ||
| # and various data-related parameters such as rows, columns, values, | ||
| # categories, and bin size. | ||
| # The visualization of the track is specified using various visual | ||
| # channels such as x, xe, row, color, and tooltip. | ||
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| single_track <- add_single_track( | ||
| id = "track1", | ||
| data = track_data( | ||
| url = cistrome_data, | ||
| type = "multivec", | ||
| row = "sample", | ||
| column = "position", | ||
| value = "peak", | ||
| categories = c("sample 1", "sample 2", "sample 3", "sample 4"), | ||
| binSize = 4, | ||
| ), | ||
| mark = "rect", | ||
| x = visual_channel_x(field = "start", type = "genomic", axis = "top"), | ||
| xe = visual_channel_x(field = "end", type = "genomic"), | ||
| row = visual_channel_row( | ||
| field = "sample", | ||
| type = "nominal", | ||
| legend = TRUE | ||
| ), | ||
| color = visual_channel_color( | ||
| field = "peak", | ||
| type = "quantitative", | ||
| legend = TRUE | ||
| ), | ||
| tooltip = visual_channel_tooltips( | ||
| visual_channel_tooltip(field = "start", type = "genomic", | ||
| alt = "Start Position"), | ||
| visual_channel_tooltip(field = "end", type = "genomic", | ||
| alt = "End Position"), | ||
| visual_channel_tooltip( | ||
| if (interactive()) { | ||
| require(shiny) | ||
| require(shiny.gosling) | ||
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| cistrome_data <- | ||
| "https://server.gosling-lang.org/api/v1/tileset_info/?d=cistrome-multivec" | ||
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| single_track <- add_single_track( | ||
| id = "track1", | ||
| data = track_data( | ||
| url = cistrome_data, | ||
| type = "multivec", | ||
| row = "sample", | ||
| column = "position", | ||
| value = "peak", | ||
| categories = c("sample 1", "sample 2", "sample 3", "sample 4"), | ||
| binSize = 4, | ||
| ), | ||
| mark = "rect", | ||
| x = visual_channel_x(field = "start", type = "genomic", axis = "top"), | ||
| xe = visual_channel_x(field = "end", type = "genomic"), | ||
| row = visual_channel_row( | ||
| field = "sample", | ||
| type = "nominal", | ||
| legend = TRUE | ||
| ), | ||
| color = visual_channel_color( | ||
| field = "peak", | ||
| type = "quantitative", | ||
| alt = "Value", | ||
| format = "0.2" | ||
| ) | ||
| ), | ||
| width = 600, | ||
| height = 130 | ||
| ) | ||
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| # The compose_view function is used to compose the single track | ||
| # visualization into a view. | ||
| # The composed view is placed within a circular layout. | ||
| # The x-domain (genomic interval) is set to chromosome 1, | ||
| # interval [1, 3000500]. | ||
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| single_composed_track <- compose_view( | ||
| tracks = single_track | ||
| ) | ||
| legend = TRUE | ||
| ), | ||
| tooltip = visual_channel_tooltips( | ||
| visual_channel_tooltip(field = "start", type = "genomic", | ||
| alt = "Start Position"), | ||
| visual_channel_tooltip(field = "end", type = "genomic", | ||
| alt = "End Position"), | ||
| visual_channel_tooltip( | ||
| field = "peak", | ||
| type = "quantitative", | ||
| alt = "Value", | ||
| format = "0.2" | ||
| ) | ||
| ), | ||
| width = 600, | ||
| height = 130 | ||
| ) | ||
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| single_composed_views <- arrange_views( | ||
| title = "Single Track", | ||
| subtitle = "This is the simplest single track visualization with a linear layout", | ||
| layout = "circular", #"linear" | ||
| views = single_composed_track, | ||
| xDomain = list( | ||
| chromosome = "chr1", | ||
| interval = c(1, 3000500) | ||
| single_composed_track <- compose_view( | ||
| tracks = single_track | ||
| ) | ||
| ) | ||
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| # The use_gosling function is used to incorporate the shiny.gosling package | ||
| # for rendering the visualization. | ||
| single_composed_views <- arrange_views( | ||
| title = "Single Track", | ||
| subtitle = "This is the simplest single track visualization with a linear layout", | ||
| layout = "circular", #"linear" | ||
| views = single_composed_track, | ||
| xDomain = list( | ||
| chromosome = "chr1", | ||
| interval = c(1, 3000500) | ||
| ) | ||
| ) | ||
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| ui <- fluidPage( | ||
| use_gosling(), | ||
| fluidRow( | ||
| column(6, goslingOutput("gosling_plot")), | ||
| column( | ||
| 1, br(), actionButton( | ||
| "download_pdf", | ||
| "PDF", | ||
| icon = icon("cloud-arrow-down") | ||
| ui <- fluidPage( | ||
| use_gosling(), | ||
| fluidRow( | ||
| column(6, goslingOutput("gosling_plot")), | ||
| column( | ||
| 1, br(), actionButton( | ||
| "download_pdf", | ||
| "PDF", | ||
| icon = icon("cloud-arrow-down") | ||
| ) | ||
| ) | ||
| ) | ||
| ) | ||
| ) | ||
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| # The renderGosling function is used to render the visualization using | ||
| # the gosling function, passing in the composed view. | ||
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| server <- function(input, output, session) { | ||
| output$gosling_plot <- renderGosling({ | ||
| gosling( | ||
| component_id = "component_1", | ||
| single_composed_views, | ||
| clean_braces = TRUE | ||
| ) | ||
| }) | ||
| server <- function(input, output, session) { | ||
| output$gosling_plot <- renderGosling({ | ||
| gosling( | ||
| component_id = "component_1", | ||
| single_composed_views, | ||
| clean_braces = TRUE | ||
| ) | ||
| }) | ||
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| observeEvent(input$download_pdf, { | ||
| export_pdf(component_id = "component_1") | ||
| }) | ||
| } | ||
| observeEvent(input$download_pdf, { | ||
| export_pdf(component_id = "component_1") | ||
| }) | ||
| } | ||
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| shinyApp(ui, server) | ||
| shinyApp(ui, server) | ||
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| } |