plotExons <- function(fit, coef = ncol(fit), geneid = NULL, genecolname = "GeneID", exoncolname = NULL, rank = 1L, FDR = 0.05)
 #	Plot log2 fold changes of the exons and mark the differentially expressed exons
 #	Yifang Hu and Gordon Smyth.
 #	Created 1 May 2014. Last modified 7 October 2014.
 {
 
 	# Check input
 	if(!is(fit, "MArrayLM")) stop("fit is not MArrayLM object")
 	if(is.null(fit$p.value)) stop("fit object should contain p value from eBayes")
 	if(is.null(fit$method)) stop("fit object should have fitting method from least square or robust regression")
 
 	genecolname <- as.character(genecolname)[1]
 	if(! (genecolname %in% colnames(fit$genes))) stop(paste("genecolname", genecolname, "not found"))
 
 	if( ! is.null(exoncolname)) {
 
 		exoncolname <- as.character(exoncolname)[1]
 		if( ! (exoncolname %in% colnames(fit$genes))) stop(paste("exoncolname", exoncolname, "not found"))
 
 	}
 
 	# Gene to plot using rank
 	if (is.null(geneid)) {
 
 		if (rank == 1L) igene <- which.min(fit$p.value[, coef])
 
 		else {
 
 			o.p <- order(fit$p.value[, coef])
 			fit.o <- fit[o.p,]
 			fit.uniq <- fit.o[!duplicated(fit.o$genes[, genecolname]),]
 			igene <- match(fit.uniq$genes[rank, genecolname], fit$genes[, genecolname])
 
 		}
 
 	# Gene to plot using geneid
 	} else {
 
 		geneid <- as.character(geneid)
 		igene <- match(geneid[1], as.character(fit$genes[, genecolname]))
 		if (is.na(igene)) stop(paste("geneid", geneid, "not found"))
 
 	}
 
 	# Gene annotation
 	ilab <- grep(paste0(genecolname, "|geneid|symbol"), colnames(fit$genes), ignore.case = TRUE)
 	genecollab <- colnames(fit$genes)[ilab]
 	genelab <- paste(sapply(fit$genes[igene,genecollab], as.character), collapse = ", ")
 
 	# Get strand if possible
 	strcol <- grepl("strand", colnames(fit$genes), ignore.case = TRUE)
 	if(any(strcol)) genelab <- paste0(genelab, " (", as.character(fit$genes[igene, strcol])[1], ")")
 
 	# Exon level DE results
 	fdr <- p.adjust(fit$p.value[, coef], method = "BH")
 	de <- data.frame(fit$genes, logFC = fit$coefficients[, coef], fdr)
 	m <- which(de[, genecolname] %in% fit$genes[igene, genecolname])
 	exon.de <- de[m,]
 
 	# Add exon identifier
 	if(is.null(exoncolname)) {
 
 		exoncolname <- "ID"
 		exon.de$ID <- 1:nrow(exon.de)
 
 	}
 
 	# Order exon level results by exon identifier
 	exon.de <- exon.de[order(exon.de[,exoncolname]),]
 
 	# Plot exons
 	plot(exon.de$logFC, xlab = "", ylab = "Log2 Fold Change", main = genelab, type = "b", xaxt = "n")
 	axis(1, at = 1:nrow(exon.de), labels = exon.de[, exoncolname], las = 2, cex.axis = 0.5)
 	mtext(text = paste("Exon", exoncolname), side = 1, padj = 5.2)
 
 	# Mark DE exons
 	mark <- exon.de$fdr < FDR
 
 	if (sum(mark) > 0) {
 
 		col <- rep(NA, nrow(exon.de))
 		col[mark & (exon.de$logFC > 0)] <- "red"
 		col[mark & (exon.de$logFC < 0)] <- "blue"
 
 		if (sum(mark) == 1) cex <- 1.5 else {
 
 			abs.fdr <- abs(log10(exon.de$fdr[mark]))
 			from <- range(abs.fdr)
 			to <- c(1, 2)
 			cex <- (abs.fdr - from[1])/diff(from) * diff(to) + to[1]
 
 		}
 
 		points((1:nrow(exon.de))[mark], exon.de$logFC[mark], col = col[mark], pch = 16, cex = cex)
 
 	}
 
 	abline(h = mean(exon.de$logFC), lty = 2)
 
 }