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dan-orig-plain-app.R
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dan-orig-plain-app.R
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library(bioDist)
library(gplots)
library(limma)
library(DT)
leftstr <- function(x, n = 1) substr(x, 1, min(n, nchar(x)))
rightstr <- function(x, n = 1) substr(x, nchar(x) - min(n - 1, nchar(x) - 1), nchar(x))
plot.null <- function()
plot(0, 0, col = "transparent", xlab = "", ylab = "", xaxt = "n", yaxt = "n", frame.plot = F)
mousecase <- function(x) paste0(toupper(substr(x, 1, 1)), tolower(substr(x, 2, nchar(x))))
ui <- fluidPage(
titlePanel("Gene Expression Comparison App"),
sidebarLayout(
div(class = "col-sm-5",
tags$form(class = "well",
selectInput("dataset", "Dataset", "GSE67985", "GSE67985", width = "30%"),
div(style="padding-bottom:3px", "Chai, Yang; Parada, Carolina; Grimaldi, Alexandre; Ho, Thach-Vu; Harunaga, Jill; Samuels, Bridget."),
div(style="padding-bottom:3px", "Distal/proximal mandible/maxilla at embryonic day 10.5/11.5/12.5/13.5/14.5, 3 replicates/condition."),
div(style="padding-bottom:7px", "Affymetrix Mouse Genome 430 2.0 Array."),
conditionalPanel("!output.datloaded",
helpText("Data is loading (may take a minute) ...")),
conditionalPanel("output.datloaded",
helpText("Data is loaded."))),
tags$form(class = "well",
checkboxGroupInput("sel", "Select",
choices = c(
"E10.5_Mnd_D", "E11.5_Mnd_D", "E12.5_Mnd_D", "E13.5_Mnd_D", "E14.5_Mnd_D",
"E10.5_Mnd_P", "E11.5_Mnd_P", "E12.5_Mnd_P", "E13.5_Mnd_P", "E14.5_Mnd_P",
"E10.5_Max_D", "E11.5_Max_D", "E12.5_Max_D", "E13.5_Max_D", "E14.5_Max_D",
"E10.5_Max_P", "E11.5_Max_P", "E12.5_Max_P", "E13.5_Max_P", "E14.5_Max_P"), inline = T)),
tags$form(class = "well",
splitLayout(cellWidths = c("35%", "65%"),
radioButtons("comp", "Compare",
choices = c(
"proximal vs. distal" = "place",
"maxilla vs. mandible" = "bone",
"age (earliest vs. latest selected)" = "age"),
selected = "place"),
list(conditionalPanel("input.comp == 'place'",
radioButtons("invert_place", br(), c("proximal down, distal up" = "normal",
"distal down, proximal up" = "inverted"), "normal", inline = T)),
conditionalPanel("input.comp == 'bone'",
radioButtons("invert_bone", list(br(), br()), c("maxilla down, mandible up" = "normal",
"mandible down, maxilla up" = "inverted"), "normal", inline = T)),
conditionalPanel("input.comp == 'age'",
radioButtons("invert_age", list(br(), br(), br(), br()),
c("earliest down, latest up" = "normal",
"latest down, earliest up" = "inverted"), "normal", inline = T))))),
tags$form(class= "well",
bootstrapPage(
div(style="display:inline-block; width:30%", textInput("fc", "Fold change cut-off", 2)),
div(style="display:inline-block", checkboxInput("log", "log2", T))),
textInput("fdr", "False discovery rate", 0.01, width = "30%"),
textInput("max", "Max. DE genes/probesets", Inf, width = "30%"),
radioButtons("summary", "For each gene, show",
choices = c("all probesets" = "Z", "most highly expressed probeset" = "A",
"most differentially expressed probeset" = "M"), selected = "Z", inline = T),
radioButtons("heatcol", "For heatmap, high values are",
choices = c("green" = "rg", "red" = "gr"), selected = "rg", inline = T)),
tags$form(class = "well",
div(tags$label("Highlight any gene/probeset in any color")),
bootstrapPage(
div(style="display:inline-block; width:18%", textInput("gene1", NULL, "name")),
div(style="display:inline-block; width:18%", textInput("gene2", NULL, "name")),
div(style="display:inline-block; width:18%", textInput("gene3", NULL, "name")),
div(style="display:inline-block; width:18%", textInput("gene4", NULL, "name")),
div(style="display:inline-block; width:18%", textInput("gene5", NULL, "name"))),
bootstrapPage(
div(style="display:inline-block; width:18%", textInput("col1", NULL, "blue")),
div(style="display:inline-block; width:18%", textInput("col2", NULL, "red")),
div(style="display:inline-block; width:18%", textInput("col3", NULL, "forestgreen")),
div(style="display:inline-block; width:18%", textInput("col4", NULL, "magenta")),
div(style="display:inline-block; width:18%", textInput("col5", NULL, "darkorange"))))),
mainPanel(width = 7,
downloadButton("download.heatmap", "Download heatmap"),
plotOutput("heatmap", height = "450px"), br(),
downloadButton("download.ma.plot", "Download MA plot"),
plotOutput("ma.plot", height = "500px"), br(),
downloadButton("download.table", "Download table"), br(), br(),
dataTableOutput("table", width = "90%"))))
server <- function(input, output){
age <- factor(rep(c(10.5, 11.5, 12.5, 13.5, 14.5), each = 12))
bone <- factor(rep(rep(c("Max", "Mnd"), each = 6), 5))
place <- relevel(factor(rep(rep(c("D", "P"), each = 3), 10)), "P")
full.design <- model.matrix(~age + bone + place)
rownames(full.design) <- paste0(age, bone, place, 1:3)
repeat{
con <- url("http://www.danielezrajohnson.com/exprs.R")
t <- try(load(con))
close(con)
if (!inherits(t, "try-error")) break}
rownames(dat) <- dat[, "probeset"]
genes.tab <- xtabs(~unlist(dat$symbol))
single.genes <- names(genes.tab)[genes.tab == 1]
output$datloaded <- reactive(is.numeric(nrow(dat)))
outputOptions(output, "datloaded", suspendWhenHidden = FALSE)
output$table <- renderDataTable({
sel <- input$sel
sel <- substr(sel, 2, nchar(sel))
sel <- gsub("_", "", sel)
sels <- character()
for (s in sel) sels <- c(sels, paste0(s, 1:3))
if (input$comp == "place"){
target.col <- "placeD"
ones <- grep("P", sels, value = T)
twos <- grep("D", sels, value = T)
ones.reduced <- gsub("P", "", ones)
twos.reduced <- gsub("D", "", twos)
ones <- ones[ones.reduced %in% twos.reduced]
twos <- twos[twos.reduced %in% ones.reduced]
invert <- ifelse(input$invert_place == "inverted", T, F)
one <- ifelse(invert, "distal", "proximal")
two <- ifelse(invert, "proximal", "distal")}
if (input$comp == "bone"){
target.col <- "boneMnd"
ones <- grep("Max", sels, value = T)
twos <- grep("Mnd", sels, value = T)
ones.reduced <- gsub("Max", "", ones)
twos.reduced <- gsub("Mnd", "", twos)
ones <- ones[ones.reduced %in% twos.reduced]
twos <- twos[twos.reduced %in% ones.reduced]
invert <- ifelse(input$invert_bone == "inverted", T, F)
one <- ifelse(invert, "mandible", "maxilla")
two <- ifelse(invert, "maxilla", "mandible")}
ages <- unique(substr(sels, 1, 4))
if (length(ages)) age.1 <- min(ages) else age.1 <- 10.5
young.col <- paste0("age", age.1)
if (input$comp == "age"){
age.2 <- max(ages)
target.col <- paste0("age", age.2)
ones <- grep(age.1, sels, value = T)
twos <- grep(age.2, sels, value = T)
ones.reduced <- gsub(age.1, "", ones)
twos.reduced <- gsub(age.2, "", twos)
ones <- ones[ones.reduced %in% twos.reduced]
twos <- twos[twos.reduced %in% ones.reduced]
invert <- ifelse(input$invert_age == "inverted", T, F)
one <- ifelse(invert, paste0("E", age.2), paste0("E", age.1))
two <- ifelse(invert, paste0("E", age.1), paste0("E", age.2))}
full.des <- full.design[c(ones, twos), ]
constant <- apply(full.des, 2, function(x) length(unique(x)) == 1)
constant[1] <- F
constant[names(constant) == young.col] <- T
design.cols <- names(constant[constant == F])
design <- data.frame(lapply(design.cols, function(x){col <- list(full.des[, x])}))
names(design) <- design.cols
control.cols <- design.cols[design.cols != target.col]
control <- data.frame(lapply(control.cols, function(x){col <- list(full.des[, x])}))
names(control) <- control.cols
if (!nrow(design) | !target.col %in% colnames(design) | !all(sels %in% c(ones, twos))) return({
output$ma.plot <- renderPlot(plot.null())
output$heatmap <- renderPlot(plot.null())
data.frame(NULL)})
dat.sel <- dat[, c(ones, twos)]
cn <- colnames(dat.sel)
if (input$summary == "A"){
dat.sel$A <- rowMeans(dat.sel)
dat.sel$P <- rownames(dat.sel)
dat.sel$symbol <- unlist(dat$symbol)
dat.single <- dat.sel[dat.sel$symbol %in% single.genes, ]
dat.multiple <- dat.sel[!dat.sel$symbol %in% single.genes, ]
dat.agg <- aggregate(A ~ symbol, dat.multiple, max)
dat.multiple <- merge(dat.agg, dat.multiple, sort = F)
rownames(dat.multiple) <- dat.multiple$P
dat.sel <- rbind(dat.single, dat.multiple)
dat.sel <- dat.sel[, cn]}
if (input$summary == "M"){
dat.sel$MM <- abs(rowMeans(dat.sel[, twos]) - rowMeans(dat.sel[, ones]))
dat.sel$P <- rownames(dat.sel)
dat.sel$symbol <- unlist(dat$symbol)
dat.single <- dat.sel[dat.sel$symbol %in% single.genes, ]
dat.multiple <- dat.sel[!dat.sel$symbol %in% single.genes, ]
dat.agg <- aggregate(MM ~ symbol, dat.multiple, max)
dat.multiple <- merge(dat.agg, dat.multiple, sort = F)
rownames(dat.multiple) <- dat.multiple$P
dat.sel <- rbind(dat.single, dat.multiple)
dat.sel <- dat.sel[, cn]}
fit <- lmFit(dat.sel, design)
efit <- eBayes(fit)
dat.sel$A <- rowMeans(dat.sel)
dat.sel$M <- rowMeans(dat.sel[, twos]) - rowMeans(dat.sel[, ones])
if (invert) dat.sel$M <- -dat.sel$M
dat.sel$symbol <- unlist(sapply(rownames(dat.sel), function(x) dat$symbol[dat$probeset == x]))
dat.sel$symbol[is.na(dat.sel$symbol)] <- rownames(dat.sel)[is.na(dat.sel$symbol)]
dat.sel$color <- "black"
dat.sel$color[dat.sel$symbol == mousecase(input$gene1) | rownames(dat.sel) == mousecase(input$gene1)] <-
tolower(input$col1)
dat.sel$color[dat.sel$symbol == mousecase(input$gene2) | rownames(dat.sel) == mousecase(input$gene2)] <-
tolower(input$col2)
dat.sel$color[dat.sel$symbol == mousecase(input$gene3) | rownames(dat.sel) == mousecase(input$gene3)] <-
tolower(input$col3)
dat.sel$color[dat.sel$symbol == mousecase(input$gene4) | rownames(dat.sel) == mousecase(input$gene4)] <-
tolower(input$col4)
dat.sel$color[dat.sel$symbol == mousecase(input$gene5) | rownames(dat.sel) == mousecase(input$gene5)] <-
tolower(input$col5)
lfc <- ifelse(input$log, abs(as.numeric(input$fc)), log2(abs(as.numeric(input$fc))))
top <- topTable(efit, coef = which(colnames(design) == target.col),
lfc = lfc, p.value = as.numeric(input$fdr), num = Inf)
top.colored <- top[rownames(top) %in% dat.sel$probeset[dat.sel$color != "black"], ]
if (nrow(top.colored)){
top.black <- top[1:min(nrow(top), as.numeric(input$max)), ]
top <- merge(top.colored, top.black, all = T)}
if (nrow(top)){
if (invert) top$logFC <- -top$logFC
top <- top[order(top$logFC, decreasing = T), ]
top$FC <- 2 ^ top$logFC
top$FC[top$logFC < 0] <- -1 / top$FC[top$logFC < 0]
top$AveExpr <- round(top$AveExpr, 3)
top$logFC <- round(top$logFC, 2)
top$FC <- round(top$FC, 2)
top$adj.P.Val <- format(top$adj.P.Val, scientific = T, digits = 2)
top$desc <- format(top$desc, justify = "left")
top$symbol <- format(top$symbol, justify = "left")
top <- top[, c("Row.names", "symbol", "AveExpr", "logFC", "FC", "adj.P.Val", "desc")]
colnames(top) <- c("Probeset", "Gene", "Ave.Expr", "Log2FC", "Fold.Change", "Adj.P.Val", "Description")}
else top <- data.frame(NULL)
dat.top <- dat.sel[rownames(dat.sel) %in% top$Probeset, ]
output$ma.plot <- renderPlot({
ma.plot <- function(){
par(mar = c(5, 5, 5, 8))
lim <- max(abs(range(dat.sel$M)))
plot(NULL, cex = 0.9,
xaxt = "n", yaxt = "n",
xlab = "Average Expression",
xlim = range(dat.sel$A),
ylim = c(-lim * 1.05, lim * 1.05),
ylab = paste0(one,
paste(rep(" ", ifelse(input$log, 15, 20)), collapse = ""),
ifelse(input$log, "Log2 Fold Change", "Fold Change"),
paste(rep(" ", ifelse(input$log, 15, 20)), collapse = ""), two),
cex.lab = 1.2, font.main = 1, cex.main = 1.2,
main = paste(unique(gsub("1$|2$|3$", "", c(ones, twos))), collapse = " "))
points(dat.sel$A[dat.sel$color == "black"], dat.sel$M[dat.sel$color == "black"], pch = 21, cex = 0.9)
points(dat.sel$A[dat.sel$color != "black"], dat.sel$M[dat.sel$color != "black"], pch = 21, cex = 0.9,
col = dat.sel$color[dat.sel$color != "black"])
if (nrow(dat.top)){
points(dat.top$A, dat.top$M, pch = 21, cex = 0.9, col = dat.top$color, bg = dat.top$color)
text(dat.top$A, dat.top$M, dat.top$symbol, col = dat.top$color,
pos = ifelse(dat.top$M > 0, 3, 1), offset = 0.4, cex = 0.9)}
ats.0 <- seq(1, 9, 1)
ats <- c(-1 * rev(ats.0), 0, ats.0)
log.labs <- ats
log.labs[log.labs > 0] <- paste0("+", log.labs[log.labs > 0])
raw.labs <- 2 ^ ats
raw.labs[raw.labs < 1] <- -1 / raw.labs[raw.labs < 1]
raw.labs[raw.labs > 1] <- paste0("+", raw.labs[raw.labs > 1])
axis(1, seq(0, 20, 1))
if (input$log) axis(2, ats, log.labs)
else axis(2, ats, raw.labs, cex.axis = ifelse(lim > 6, 0.75, 1))
abline(h = lfc * c(-1, 1), lty = 2)}
plotPNG(ma.plot, "ma.plot.png", width = 2000, height = 1000, res = 300)
ma.plot()
})
output$download.ma.plot <- downloadHandler("Facebase_Microarray_MA_Plot.png",
function(file) file.copy("ma.plot.png", file))
output$heatmap <- renderPlot({
heatmap <- function(){
withProgress({
if (nrow(dat.top) < 2) return(plot.null())
dat.heat <- as.matrix(dat.top[, sels])
for (col in colnames(control)){
for (v in unique(control[, col])){
mm <- mean(dat.heat[, rownames(control)[control[, col] == v]])
dat.heat[, rownames(control)[control[, col] == v]] <-
dat.heat[, rownames(control)[control[, col] == v]] - mm}}
dat.heat <- sweep(dat.heat, 1, rowMeans(dat.heat))
weights <- (ncol(dat.heat):1) + 10000
weights[colnames(dat.heat) %in% twos] <-
weights[colnames(dat.heat) %in% twos] + ifelse(invert, -100, 100)
if (input$log) extreme <- max(abs(dat.top$M)) / 2
else extreme <- 2 ^ max(abs(dat.top$M)) / 2
extreme <- ceiling(10 * extreme) / 10
heatmap.2(t(dat.heat),
Rowv = as.integer(weights),
col = ifelse(input$heatcol == "rg", redgreen, greenred),
cexCol = min(1.5, 0.2 + 1/log10(nrow(dat.heat))),
scale = "none", key = T, key.title = NA, lwid = c(1, 4), lhei = c(1.5, 4),
density.info = "density", densadj = 0.5, denscol = "white",
key.ylab = NA, key.xlab = ifelse(input$log, "Log2 Fold Change", "Fold Change"),
key.par = list(cex.lab = 1.25, cex.axis = 1, tcl = -0.35, mgp = c(2, 1, 0)),
key.ytickfun = function() list(labels = F, tick = F),
key.xtickfun = function(){
breaks <- parent.frame()$breaks
list(at = c(0, 0.2, 0.4, 0.6, 0.8, 1),
labels = round(seq(-extreme, extreme, length = 6), 1),
padj = -0.25)},
trace = "none", margins = c(5, 10),
distfun = function(...) cor.dist(..., abs = F),
labCol = dat.top$symbol, colCol = dat.top$color)
incProgress(1)}, value = NULL, message = "Calculations in progress...")}
plotPNG(heatmap, "heatmap.png", width = 2000, height = 1000, res = 300)
heatmap()
})
output$download.heatmap <- downloadHandler("Facebase_Microarray_Heatmap.png",
function(file) file.copy("heatmap.png", file))
rownames(top) <- NULL
output$download.table <- downloadHandler("Facebase_Microarray_Table.csv",
function(file) write.csv(as.data.frame(top), file, row.names = F))
top$Color <- unlist(sapply(top$Probeset, function(x) dat.top$color[rownames(dat.top) == x]))
top <- formatStyle(datatable(top), "Color", target = "row",
color = styleEqual(
c(0, input$col1, input$col2, input$col3, input$col4, input$col5),
c("white", input$col1, input$col2, input$col3, input$col4, input$col5)))
})
}
shinyApp(ui = ui, server = server)