inst/doc/h5vc.simple.genome.browser.R

In h5vc: Managing alignment tallies using a hdf5 backend

## ---- eval=FALSE--------------------------------------------------------------
#  library(shiny)
#  shinyUI(pageWithSidebar(
#    # Application title
#    headerPanel("Simple Genome Browser"),
#    # Sidebar with a slider inputs and selection boxes
#    sidebarPanel(
#      sliderInput("windowsize",
#                  "Windowsize:",
#                  min = 10,
#                  max = 200,
#                  value = 50,
#                  step = 5),
#      uiOutput("chromSelect"),
#      uiOutput("genomicPositionSelect")
#    ),
#    # Show a plot of the region
#    mainPanel(
#      plotOutput("mismatchPlot", height=800)
#    )
#  ))

## ---- eval=FALSE--------------------------------------------------------------
#  library(shiny)
#  library(h5vc)
#  library(rhdf5)
#  tallyFile <- "yeast.hfs5"
#  study <- "/yeast"
#  h5ls( tallyFile )
#  chromosomes  <- h5ls( tallyFile )
#  chromlengths <- as.numeric(subset( chromosomes, otype == "H5I_DATASET" & name == "Reference" )$dim)
#  chromosomes  <- subset( chromosomes, otype == "H5I_GROUP" & name != "yeast" )$name
#  names(chromlengths) = chromosomes
#  
#  # Define server logic required to generate and plot a random distribution
#  shinyServer(function(input, output) {
#  
#    output$chromSelect <- renderUI({
#      selectInput( "chrom", "Chromosome", choices = c("I","II","III","IV","V","VI","VII","VIII","IX","X","XI","XII","XIII","XIV","XV","XVI", "Mito"))
#    })
#  
#    output$genomicPositionSelect <- renderUI({
#      sliderInput( "gpos", "Genomic Position:", min = 10, max = chromlengths[input$chrom] - 10, value = 200 )
#    })
#  
#    group <- reactive({ paste( study, input$chrom, sep="/" ) })
#  
#    sampleData <- reactive({ sd = getSampleData( tallyFile, group() ); sd$Sample = c("YB210","s288c"); sd })
#  
#    pos <- reactive({
#      min( max( input$windowsize + 1, input$gpos ), chromlengths[input$chrom] - input$windowsize - 1 )
#    })
#  
#    data <- reactive({
#      h5dapply(
#        tallyFile,
#        group(),
#        blocksize = input$windowsize*3,
#        names = c("Coverages","Counts","Deletions"),
#        range = c( max( pos() - input$windowsize, 0 ), min( pos() + input$windowsize, chromlengths[input$chrom] )  )
#      )[[1]]
#  
#    })
#  
#    output$mismatchPlot <- renderPlot({
#      p = mismatchPlot(
#        data(),
#        sampleData(),
#        samples = c("s288c","YB210"),
#        input$windowsize,
#        pos()
#        )
#      print(p)
#    })
#  })

## ---- eval=FALSE--------------------------------------------------------------
#  library(rhdf5)
#  library(h5vc)
#  setwd("~/ShinyApps/Yeast")
#  tallyFile <- "yeast.hfs5"
#  study <- "/yeast"
#  h5ls( tallyFile )
#  chromosomes <- h5ls( tallyFile )
#  chromosomes <- subset( chromosomes, otype == "H5I_GROUP" & name != "yeast" )$name
#  variantCalls <- list()
#  for( chrom in chromosomes ){
#    group <- paste( study, chrom, sep = "/" )
#    sdat <- getSampleData( tallyFile, group )
#    sdat$Group <- "yeast"
#    variantCalls[[chrom]] <- h5dapply(
#      filename = tallyFile,
#      group = group,
#      blocksize = 100000,
#      FUN = callVariantsPairedFancy,
#      sampledata = sdat,
#      cl = vcConfParams( returnDataPoints = TRUE, minStrandAltSupport = 4 ),
#      names = c( "Counts", "Coverages", "Reference" ),
#      verbose = TRUE
#    )
#  }
#  for( chrom in chromosomes ){
#    variantCalls[[chrom]] <- do.call( rbind, variantCalls[[chrom]] )
#  }
#  variantCalls <- do.call( rbind, variantCalls )
#  rownames(variantCalls) = NULL
#  variantCalls$Support = variantCalls$caseCountFwd + variantCalls$caseCountRev
#  variantCalls$Coverage = variantCalls$caseCoverageFwd + variantCalls$caseCoverageRev
#  variantCalls$AF = variantCalls$Support / variantCalls$Coverage
#  save( variantCalls, file = "yeast.variants.RDa" )

## ---- eval=FALSE--------------------------------------------------------------
#  library(shiny)
#  shinyUI(pageWithSidebar(
#  
#    # Application title
#    headerPanel("Simple Variant Browser - Yeast Strains Example"),
#  
#    # Sidebar with a slider inputs and selection boxes
#    sidebarPanel(
#      sliderInput("windowsize",
#                  "Windowsize:",
#                  min = 10,
#                  max = 200,
#                  value = 50,
#                  step = 5),
#      uiOutput("chromSelect"),
#      sliderInput("af",
#                  "Allele Frequency:",
#                  min = 0,
#                  max = 1,
#                  value = c(0.1,1.0),
#                  step = 0.01),
#      sliderInput( "minSupport",
#                   "Minimum Support",
#                   min = 2,
#                   max = 200,
#                   value = 2),
#      sliderInput( "minCoverage",
#                   "Minimum Coverage",
#                   min = 10,
#                   max = 500,
#                   value = 50,
#                   step = 5),
#      uiOutput("variantSelect"),
#      textOutput("diag")
#    ),
#  
#    # Show a plot of the region
#    mainPanel(
#      tabsetPanel(
#        tabPanel( title = "Region Mismatch Plot", plotOutput("mismatchPlot", height=800) ),
#        tabPanel( title = "Variant Table", tableOutput("variantTable") ),
#        tabPanel( title = "Variant Summary Plots", plotOutput("afHist") )
#      )
#    )
#  ))

## ---- eval=FALSE--------------------------------------------------------------
#  library(shiny)
#  library(h5vc)
#  library(rhdf5)
#  library(ggplot2)
#  library(grid)
#  
#  tallyFile <- "yeast.hfs5"
#  study <- "/yeast"
#  h5ls( tallyFile )
#  chromosomes  = h5ls( tallyFile )
#  chromlengths = as.numeric(subset( chromosomes, otype == "H5I_DATASET" & name == "Reference" )$dim)
#  chromosomes  = subset( chromosomes, otype == "H5I_GROUP" & name != "yeast" )$name
#  names(chromlengths) = chromosomes
#  
#  load(file="yeast.variants.RDa")
#  variantCalls$start <- variantCalls$start + 1 #fixing difference in counting 0-based vs. 1-based
#  variantCalls$end <- variantCalls$end + 1
#  # Define server logic required to generate and plot a random distribution
#  shinyServer(function(input, output) {
#  
#    output$chromSelect <- renderUI({
#      selectInput( "chrom", "Chromosome", choices = c("I","II","III","IV","V","VI","VII","VIII","IX","X","XI","XII","XIII","XIV","XV","XVI", "Mito"))
#    })
#  
#    group <- reactive({ paste( study, input$chrom, sep="/" ) })
#  
#    sampleData <- reactive({ sd = getSampleData( tallyFile, group() ); sd$Sample = c("YB210","s288c"); sd })
#  
#    variants <- reactive({
#      subset( variantCalls, seqnames == input$chrom & AF >= input$af[1] & AF <= input$af[2] & Support >= input$minSupport & Coverage >= input$minCoverage )
#    })
#  
#    output$variantSelect <- renderUI({
#      tmp = seq(nrow(variants()))
#      names(tmp) =  paste( variants()$start, " - ", variants()$refAllele, "/", variants()$altAllele, sep="" )
#      selectInput( "var", "Variant:", choices = tmp )
#    })
#  
#    pos <- reactive({
#      variants()$start[as.numeric(input$var)]
#    })
#  
#    data <- reactive({
#      if( nrow(variants()) > 0 ){
#        h5dapply(
#          filename = tallyFile,
#          group = group(),
#          blocksize = input$windowsize*3,
#          names = c("Coverages","Counts","Deletions"),
#          range = c( max( pos() - input$windowsize, 0 ), min( pos() + input$windowsize, chromlengths[input$chrom] )  )
#        )[[1]]
#      }else{
#        NULL
#      }
#    })
#  
#    output$mismatchPlot <- renderPlot({
#      if( nrow(variants()) > 0 ){
#        p = mismatchPlot(
#          data(),
#          sampleData(),
#          samples = c("s288c","YB210"),
#          input$windowsize,
#          pos()
#        )
#        print(p)
#      }
#    })
#  
#    output$variantTable <- renderTable({
#      variants()[,c("seqnames", "start", "refAllele", "altAllele", "AF", "Support", "Coverage")]
#    })
#  
#    output$afHist = renderPlot({
#      hist( variants()$AF, breaks = seq(0,1,0.01) )
#    })
#  
#  })