using shiny with readVcf, predictCoding, ...

gistfile1.txt

library(shiny) # works with the chr22.vcf.gz in the VariantAnnotation extdata
library(dplyr)
library(DT)
library(VariantAnnotation)
library(BSgenome.Hsapiens.UCSC.hg19)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

ui <- fluidPage(
  titlePanel("VCF XPLORR"),
  numericInput("numvar", "num2chk", value = 50, min = 50, max = 500, step = 10),
  fileInput("fileInput", "Choose a VCF file",
    accept = c(".vcf", ".vcf.gz", ".maf"),
    multiple = FALSE
  ),
  DTOutput("table")
)

server <- function(input, output, session) {
  options(shiny.maxRequestSize = 40 * 1024^2)

  output$table <- renderDataTable({
    validate(need(!is.null(input$fileInput$datapath), "please pick file"))
    raw_vcf_data <- readVcf(input$fileInput$datapath, "hg19")
    # Perform filtering based on the FILTER column

    # filtered_vcf_data <- subset(raw_vcf_data, FILTER == "PASS")
    myv <- as(raw_vcf_data, "VRanges")[seq_len(input$numvar)]
    # seqlevelsStyle(myv) = "UCSC" # FIXME!
    seqlevels(myv) <- paste0("chr", seqlevels(myv))
    coding <- predictCoding(myv, txdb, seqSource = Hsapiens, DNAStringSet(alt(myv)))

    as.data.frame(coding)
  })
}

shinyApp(ui = ui, server = server)