In this vignette, we will build a shiny app to visualize RangeSummarizedExperiment using epivizrChart. Since epiviz visualization library is built upon the web components framework, it can be integrated with most frameworks that support HTML.

Sample data sets to use for the vignette.

data(sumexp)

We create an Environment element which visualizes genome wide data. We then visualize cancer and normal values from the SummarizedExperiment object.

epivizEnv <- epivizEnv(interactive = TRUE)
scatterplot <- epivizEnv$plot(sumexp, datasource_name="sumExp", columns=c("cancer", "normal"))

After looking at the genomic wide data, if you are interested in further exploring a specific region of the genome, We can create a navigation element linked to that genomic location. We can plot additional annotation/data charts/tracks in this region.

epivizNav <- epivizNav(chr="chr11", start=118000000, end=121000000, parent=epivizEnv, interactive = TRUE)

genes_track <- epivizNav$add_genome(Homo.sapiens, datasource_name="genes")

## creating gene annotation (it may take a bit)

## 'select()' returned 1:1 mapping between keys and columns

# region_scatterplot <- epivizNav$plot(sumexp, datasource_name="sumExp", columns=c( "cancer", "normal"))
region_linetrack <- epivizNav$plot(sumexp, datasource_name="sumExp", columns=c( "cancer", "normal"), chart="LineTrack")

Finally, we can embed these components in a Shiny App.

app <- shinyApp(
  ui=fluidPage(
    uiOutput("epivizChart")
  ),
  server=function(input, output, session) {
    
    output$epivizChart <- renderUI({
      epivizEnv$render_component(shiny=TRUE)
    })
    
    epivizEnv$register_shiny_handler(session)
  }
)

app