R/plotGene.R
In bernatgel/genoploteR:
#' plotGene
#'
#' @description
#'
#' Plots the main title of the plot
#'
#' @details
#'
#' @usage plotGene()
#'
#' @param genoplot a \code{GenoPlot} object returned by a call to \code{plotGene}
#' @param main (character) the main title of the plot
#' @param ... any additional parameter to be passed to the text plotting. All R base graphics params are passed along.
#'
#' @return
#' invisibly returns the given GenoPlot object
#'
#' @seealso \code{\link{gpAddMainTitle}}
#'
#' @examples
#'
#'
#'
#'
#' @export plotGene
#'
#' @import karyoploteR
#' @importFrom S4Vectors DataFrame
#' @importFrom GenomicRanges sort
addMargins <- function(regs, inner.margin, outer.margin) {
regs <- extendRegions(regs, inner.margin, inner.margin)
regs[1] <- extendRegions(regs[1], extend.start = outer.margin - inner.margin)
regs[length(regs)] <- extendRegions(regs[length(regs)], extend.end = outer.margin - inner.margin)
return(regs)
}
selectPlotType <- function(show.introns=FALSE, compress.introns=TRUE, proportional.introns=TRUE) {
if(show.introns==FALSE) return("only.exons")
if(compress.introns==FALSE) return("all")
if(proportional.introns==TRUE) return("compressed.introns.proportional")
else return("compressed.introns.all.equal")
}
#If the function name is plotGene, regions should be called exons.
#In any case it should accept a list of GRanges (or GRangesList) with
#coding and non-coding exons or a TxDb and transcript name?
#Or maybe the trasformation from transcript should be done outside
#in an exernal function
plotGene <- function(exons, show.introns=FALSE, compress.introns=TRUE, proportional.introns=TRUE, intron.to.exon.ratio=0.1, intron.length=200, main=NULL, plot.params=NULL, gene.plotter=gpAddGeneStructure, ...) {
#TODO: Check parameters
plot.type <- selectPlotType(show.introns=show.introns, compress.introns=compress.introns, proportional.introns=proportional.introns)
#Get plot params given the plot.type
if(is.null(plot.params)) {
plot.params <- getDefaultPlotParams(show.introns=show.introns, compress.introns=compress.introns, proportional.introns=proportional.introns)
}
exons <- GenomicRanges::sort(toGRanges(exons)) #So it's possible to give them in any valid format
total.gene.region <- regioneR::toGRanges(seqnames(exons[1]), start(exons[1]), end(exons[length(exons)]))
introns <- regioneR::subtractRegions(total.gene.region, exons)
introns$type <- "intron"
#TODO: If the intron between two exons is shorter than twice the inner margin, join the exons (and the intron) into a single region
#TODO: To implement a zoom, we should intersect the exons (and introns!) with the zoom region and continue as usual but keeping their mcols
#Compute the region size values for the selected plot.type
#Case 1: only exons visible (remove introns)
if(plot.type=="only.exons") {
ex.regs <- regioneR::joinRegions(exons, min.dist = 1)
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
exons.space.per.base <- available.space/sum(width(ex.regs))
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
regions <- ex.regs #Plot only the exons
} else if(plot.type=="compressed.introns.proportional") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- sum(width(in.regs))
adjusted.total.bases <- exons.bases + introns.bases*intron.to.exon.ratio
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base*intron.to.exon.ratio
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else if(plot.type=="compressed.introns.all.equal") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- length(in.regs)*intron.length
adjusted.total.bases <- exons.bases + introns.bases
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base*intron.length/width(in.regs)
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else if(plot.type=="all") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- sum(width(in.regs))
adjusted.total.bases <- exons.bases + introns.bases
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else {
stop("Invalid plot.type ", plot.type)
}
#At this point we have a "regions" GRanges object with the plotted regions and for each one a space.per.base value
#Create the GenoPlot object to return
gp <- list()
class(gp) <- "GenoPlot"
#and set some of its elements
gp$plot.params <- plot.params
gp$plot.type <- plot.type
gp$exons <- exons
gp$introns <- introns
gp$total.plot.region <- extendRegions(total.gene.region, extend.start = plot.params$outer.margin.bases, extend.end = plot.params$outer.margin.bases)
gp$regions <- regions
gp$chromosome <- as.character(seqnames(regions)[1])
#TODO: Decide how to manage the genome specification. Should we use a genome? Could be useful if we want to automatically add the sequence...
#Create a custom genome for karyoploteR with the plot region only (will speed up some functions)
cust.genome <- gp$total.plot.region
#Create the plot
#Start creating an empty karyoplot (zoomed in on the correct chromosome) and get the KaryoPlot object
gp$global.kp <- karyoploteR::plotKaryotype(zoom=exons[1], plot.type=2, labels.plotter = NULL, ideogram.plotter = NULL, plot.params=plot.params, genome=cust.genome) #The zoom used here is not used to plot anything, but sets kp in the correct state
#And prepare the list of KaryoPlot objects needed to plot
#Now create a modified copy of this KaryoPlot adapted to each plotted region
gp$regions.kp <- list()
#Iteratively make the left margin bigger to plot each region at its position
last.region.end <- gp$global.kp$plot.params$leftmargin - plot.params$margin.between.regions #The first region will cancel this between regions margin
for(num.reg in seq_len(length(regions))) {
r <- regions[num.reg]
region.size <- width(r)*r$space.per.base
left.margin <- last.region.end + plot.params$margin.between.regions
right.margin <- 1 - left.margin - region.size
last.region.end <- 1 - right.margin
#Build the region specific karyoplot
reg.kp <- gp$global.kp
#Set the plot.params
reg.kp$plot.params <- gp$global.kp$plot.params
reg.kp$plot.params$leftmargin <- left.margin
reg.kp$plot.params$rightmargin <- right.margin
#Set the plot region
names(r) <- as.character(seqnames(r)) #needed for various karyoploteR functions
reg.kp$plot.region <- r
#Update the coordinate change functions
#Warning: using triple semicolon to access the PRIVATE function from karyoploteR.
#Doing it so it's not necessary for karyoploteR to export that function, which would
#be only useful in extremely hacky use cases like this one
reg.kp$coord.change.function <- karyoploteR:::getCoordChangeFunctions(reg.kp)$coordChangeFunction
#Store the new kp in the list
class(reg.kp) <- "KaryoPlot"
gp$regions.kp[[num.reg]] <- reg.kp
}
#Set some more elements in the GenoPlot object
gp$beginGpPlot <- gp$global.kp$beginKpPlot
gp$endGpPlot <- gp$global.kp$endGpPlot
#At this point the gp object is finished.
#As a convenience (and to not create an empty plot by default) optionally plot a few elements
#TODO: Plot the exon/intron structure
if(!is.null(gene.plotter)) {
gene.plotter(gp, ...)
}
#TODO: Plot the name of the gene/transcript...
#Plot the main title
if(!is.null(main)) {
gpAddMainTitle(gp, main=main, ...)
}
#Everything finished. Return the GenoPlot object
return(gp)
}
bernatgel/genoploteR documentation built on May 13, 2019, 5:22 p.m.
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#' plotGene
#'
#' @description
#'
#' Plots the main title of the plot
#'
#' @details
#'
#' @usage plotGene()
#'
#' @param genoplot a \code{GenoPlot} object returned by a call to \code{plotGene}
#' @param main (character) the main title of the plot
#' @param ... any additional parameter to be passed to the text plotting. All R base graphics params are passed along.
#'
#' @return
#' invisibly returns the given GenoPlot object
#'
#' @seealso \code{\link{gpAddMainTitle}}
#'
#' @examples
#'
#'
#'
#'
#' @export plotGene
#'
#' @import karyoploteR
#' @importFrom S4Vectors DataFrame
#' @importFrom GenomicRanges sort
addMargins <- function(regs, inner.margin, outer.margin) {
regs <- extendRegions(regs, inner.margin, inner.margin)
regs[1] <- extendRegions(regs[1], extend.start = outer.margin - inner.margin)
regs[length(regs)] <- extendRegions(regs[length(regs)], extend.end = outer.margin - inner.margin)
return(regs)
}
selectPlotType <- function(show.introns=FALSE, compress.introns=TRUE, proportional.introns=TRUE) {
if(show.introns==FALSE) return("only.exons")
if(compress.introns==FALSE) return("all")
if(proportional.introns==TRUE) return("compressed.introns.proportional")
else return("compressed.introns.all.equal")
}
#If the function name is plotGene, regions should be called exons.
#In any case it should accept a list of GRanges (or GRangesList) with
#coding and non-coding exons or a TxDb and transcript name?
#Or maybe the trasformation from transcript should be done outside
#in an exernal function
plotGene <- function(exons, show.introns=FALSE, compress.introns=TRUE, proportional.introns=TRUE, intron.to.exon.ratio=0.1, intron.length=200, main=NULL, plot.params=NULL, gene.plotter=gpAddGeneStructure, ...) {
#TODO: Check parameters
plot.type <- selectPlotType(show.introns=show.introns, compress.introns=compress.introns, proportional.introns=proportional.introns)
#Get plot params given the plot.type
if(is.null(plot.params)) {
plot.params <- getDefaultPlotParams(show.introns=show.introns, compress.introns=compress.introns, proportional.introns=proportional.introns)
}
exons <- GenomicRanges::sort(toGRanges(exons)) #So it's possible to give them in any valid format
total.gene.region <- regioneR::toGRanges(seqnames(exons[1]), start(exons[1]), end(exons[length(exons)]))
introns <- regioneR::subtractRegions(total.gene.region, exons)
introns$type <- "intron"
#TODO: If the intron between two exons is shorter than twice the inner margin, join the exons (and the intron) into a single region
#TODO: To implement a zoom, we should intersect the exons (and introns!) with the zoom region and continue as usual but keeping their mcols
#Compute the region size values for the selected plot.type
#Case 1: only exons visible (remove introns)
if(plot.type=="only.exons") {
ex.regs <- regioneR::joinRegions(exons, min.dist = 1)
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
exons.space.per.base <- available.space/sum(width(ex.regs))
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
regions <- ex.regs #Plot only the exons
} else if(plot.type=="compressed.introns.proportional") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- sum(width(in.regs))
adjusted.total.bases <- exons.bases + introns.bases*intron.to.exon.ratio
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base*intron.to.exon.ratio
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else if(plot.type=="compressed.introns.all.equal") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- length(in.regs)*intron.length
adjusted.total.bases <- exons.bases + introns.bases
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base*intron.length/width(in.regs)
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else if(plot.type=="all") {
internal.margin <- plot.params$margin.between.regions*(length(exons)-1)
available.space <- 1 - plot.params$leftmargin - plot.params$rightmargin - internal.margin
ex.regs <- regioneR::joinRegions(exons, min.dist = 1) #Join contiguous coding and non-coding exons into single regions
ex.regs <- addMargins(ex.regs, inner.margin = plot.params$inner.margin.bases, outer.margin = plot.params$outer.margin.bases)
in.regs <- regioneR::extendRegions(introns, -1*plot.params$inner.margin.bases, -1*plot.params$inner.margin.bases)
exons.bases <- sum(width(ex.regs))
introns.bases <- sum(width(in.regs))
adjusted.total.bases <- exons.bases + introns.bases
exons.space.per.base <- available.space/adjusted.total.bases
introns.space.per.base <- exons.space.per.base
mcols(ex.regs) <- S4Vectors::DataFrame(space.per.base=exons.space.per.base)
mcols(in.regs) <- S4Vectors::DataFrame(space.per.base=introns.space.per.base)
regions <- GenomicRanges::sort(c(ex.regs, in.regs))
} else {
stop("Invalid plot.type ", plot.type)
}
#At this point we have a "regions" GRanges object with the plotted regions and for each one a space.per.base value
#Create the GenoPlot object to return
gp <- list()
class(gp) <- "GenoPlot"
#and set some of its elements
gp$plot.params <- plot.params
gp$plot.type <- plot.type
gp$exons <- exons
gp$introns <- introns
gp$total.plot.region <- extendRegions(total.gene.region, extend.start = plot.params$outer.margin.bases, extend.end = plot.params$outer.margin.bases)
gp$regions <- regions
gp$chromosome <- as.character(seqnames(regions)[1])
#TODO: Decide how to manage the genome specification. Should we use a genome? Could be useful if we want to automatically add the sequence...
#Create a custom genome for karyoploteR with the plot region only (will speed up some functions)
cust.genome <- gp$total.plot.region
#Create the plot
#Start creating an empty karyoplot (zoomed in on the correct chromosome) and get the KaryoPlot object
gp$global.kp <- karyoploteR::plotKaryotype(zoom=exons[1], plot.type=2, labels.plotter = NULL, ideogram.plotter = NULL, plot.params=plot.params, genome=cust.genome) #The zoom used here is not used to plot anything, but sets kp in the correct state
#And prepare the list of KaryoPlot objects needed to plot
#Now create a modified copy of this KaryoPlot adapted to each plotted region
gp$regions.kp <- list()
#Iteratively make the left margin bigger to plot each region at its position
last.region.end <- gp$global.kp$plot.params$leftmargin - plot.params$margin.between.regions #The first region will cancel this between regions margin
for(num.reg in seq_len(length(regions))) {
r <- regions[num.reg]
region.size <- width(r)*r$space.per.base
left.margin <- last.region.end + plot.params$margin.between.regions
right.margin <- 1 - left.margin - region.size
last.region.end <- 1 - right.margin
#Build the region specific karyoplot
reg.kp <- gp$global.kp
#Set the plot.params
reg.kp$plot.params <- gp$global.kp$plot.params
reg.kp$plot.params$leftmargin <- left.margin
reg.kp$plot.params$rightmargin <- right.margin
#Set the plot region
names(r) <- as.character(seqnames(r)) #needed for various karyoploteR functions
reg.kp$plot.region <- r
#Update the coordinate change functions
#Warning: using triple semicolon to access the PRIVATE function from karyoploteR.
#Doing it so it's not necessary for karyoploteR to export that function, which would
#be only useful in extremely hacky use cases like this one
reg.kp$coord.change.function <- karyoploteR:::getCoordChangeFunctions(reg.kp)$coordChangeFunction
#Store the new kp in the list
class(reg.kp) <- "KaryoPlot"
gp$regions.kp[[num.reg]] <- reg.kp
}
#Set some more elements in the GenoPlot object
gp$beginGpPlot <- gp$global.kp$beginKpPlot
gp$endGpPlot <- gp$global.kp$endGpPlot
#At this point the gp object is finished.
#As a convenience (and to not create an empty plot by default) optionally plot a few elements
#TODO: Plot the exon/intron structure
if(!is.null(gene.plotter)) {
gene.plotter(gp, ...)
}
#TODO: Plot the name of the gene/transcript...
#Plot the main title
if(!is.null(main)) {
gpAddMainTitle(gp, main=main, ...)
}
#Everything finished. Return the GenoPlot object
return(gp)
}
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