Package 'karyoploteR'

Description

Adds the gene names (defaults to symbols) to a GenesData object to be used by kpPlotGenes

Usage

addGeneNames(genes.data, orgDb="auto", keys=NULL, keytype="ENTREZID", names="SYMBOL")

Arguments

Details

This function takes a valid data object and uses an OrgDb object to find the gene names (symbols by default) and add them. Names are added as a column named names to the genes element of GenesData and they replace anything that was present there before. If no ObjDb object is given, the function will try to identify the correct organism using the data in GenesData$metadata and select the OrgDb object if available. If it cannot identify the organism or there's no valid OrgDb for that organism it will fail with an error. Internally, the function uses a call to AnnotationDbi::select on the OrgDb. It is possible to specify the keys and keytypes as well as the column we want to use as names (defaults to SYMBOL for gene symbols).

Value

The original GenesData object with one additional column named "names" in GenesData$genes$names.

See Also

kpPlotGenes, makeGenesDataFromTxDb

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)

zoom <- toGRanges("chr17:29e6-30e6")
kp <- plotKaryotype(genome="hg19", zoom=zoom)
genes.data <- makeGenesDataFromTxDb(TxDb.Hsapiens.UCSC.hg19.knownGene, 
                 karyoplot=kp, plot.transcripts=FALSE,
                 plot.transcripts.structure=FALSE)
genes.data <- addGeneNames(genes.data)
kpPlotGenes(kp, data=genes.data, r1=0.5, plot.transcripts=FALSE,
            gene.name.position = "left")

Description

Computes r0 and r1 given track definition

Usage

autotrack(current.track, total.tracks, margin=0.05, r0=0, r1=1)

Arguments

Details

Small utility function to help compute r0 and r1 given the total number of tracks and the track(s) the current plot will occupy. It also takes into account a margin between tracks and original r0 and r1, so we can say something like, "Out of 5 tracks between 0 and 0.5, this plot will be at track 2", and it will return r0=0.1 and r1=0.2

Value

A list of two numerics: r0 and r1

Examples

#first track out of 4  
autotrack(1, 4)

#the same, but without margin
autotrack(1, 4, 0)

#first and second tracks out of 4
autotrack(c(1,2), 4)

#The first track out of 4, fitting the four track between 0 and 0.5
autotrack(1, 4, r0=0, r1=0.5)

Description

Given a vector of categorical values, assign a color to each one bases on its category

Usage

colByCategory(categories, colors)

Arguments

Details

The vector of values will be first transformed into a factor (if it's not already a factor) and then colors will be selected from the palette in the order defined by the factor levels. If more colors than the ones available in the palette are needed, they will be reused. If the color vector is named using the factor levels and all levels are included, the link bewteen levels and colors will be honored. If the color palette is set to "auto", it will create a palette using "rainbow".

Value

A vector of colors of the same length as value

See Also

kpAddColorRect, colByValue

Examples

colByCategory(c("A", "A", "C", "A", "C", "B"))
#The order of the colors is defined by the order of the factor, not the "natural order" of the elements
colByCategory(c("A", "A", "C", "A", "C", "B"), colors=c("red", "green", "blue"))
#integer categories plus reuse of colors
colByCategory(categories=c(3,3,1,2,1,4,2,3,2,1), colors=c("red", "green", "blue"))

Description

Given a set of data elements, return a color for each one based on their chromosome

Usage

colByChr(data, colors="2grays", all.chrs=NULL, default.col="black")

Arguments

Details

Returns a color for each data element based on its chromosome. The returned colors might com from one of the predefined color sets or passed in as a parameter.

If colors is the name of one of the available color sets, it the color set is used. If it's a named character vector with the chromosome as names, they will be assigned by name and any missing chromosome will be default.col. If it's a non-named chraracter vector, will be used in order and recycled if necessary.

Data might be either a GRanges object or a vector of chromosomes.

Value

A vector of colors

Note

Available color.sets: "2grays"=c("#888888", "#444444"), "2blues"=c("#6caeff", "#2b5d9b") "blackgreen"=c("black", "green"), "greengray"=c("#c6ffb7", "#888888"), "brewer.set1"=c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999") "brewer.set2"=c("#66C2A5", "#FC8D62", "#8DA0CB", "#E78AC3", "#A6D854", "#FFD92F", "#E5C494", "#B3B3B3") "brewer.set3"=c("#8DD3C7", "#FFFFB3", "#BEBADA", "#FB8072", "#80B1D3", "#FDB462", "#B3DE69", "#FCCDE5", "#D9D9D9", "#BC80BD", "#CCEBC5", "#FFED6F") "brewer.pastel1"=c("#FBB4AE", "#B3CDE3", "#CCEBC5", "#DECBE4", "#FED9A6", "#FFFFCC", "#E5D8BD", "#FDDAEC", "#F2F2F2"), "brewer.pastel2"=c("#B3E2CD", "#FDCDAC", "#CBD5E8", "#F4CAE4", "#E6F5C9", "#FFF2AE", "#F1E2CC", "#CCCCCC"), "rainbow"=rainbow(n=length(all.chrs))

See Also

kpPoints

Examples

chrs <- c("chr1", "chr2", "chr2", "chr1", "chr5")
points <- toGRanges(paste0("chr", c(1:22, "X", "Y")), rep(10e6, 24), rep(10e6, 24))

colByChr(chrs)
colByChr(points)

kp <- plotKaryotype(plot.type=4, labels.plotter=NULL, ideogram.plotter=NULL)
kpAddChromosomeNames(kp, srt=45)
kpAddChromosomeSeparators(kp)

total.tracks <- 6

kpPoints(kp, points, col=colByChr(points), y=0.5, cex=1, r0=autotrack(1,total.tracks)$r0, r1=autotrack(1,total.tracks)$r1)
colors <- NULL
kpPoints(kp, points, y=0.5, col=colByChr(points, colors=colors), cex=1, r0=autotrack(2,total.tracks)$r0, r1=autotrack(2,total.tracks)$r1)
colors <- c("red", "blue")
kpPoints(kp, points, y=0.5, col=colByChr(points, colors=colors), cex=1, r0=autotrack(3,total.tracks)$r0, r1=autotrack(3,total.tracks)$r1)
colors <- c(chr1="red", chr7="blue")
kpPoints(kp, points, y=0.5, col=colByChr(points, colors=colors), cex=1, r0=autotrack(4,total.tracks)$r0, r1=autotrack(4,total.tracks)$r1)
kpPoints(kp, points, y=0.5, col=colByChr(points, colors=colors, default.col="green"), cex=1, r0=autotrack(5,total.tracks)$r0, r1=autotrack(5,total.tracks)$r1)
colors <- c("red", "yellow", 3, "orchid", "blue")
kpPoints(kp, points, y=0.5, col=colByChr(points, colors=colors), cex=1, r0=autotrack(6,total.tracks)$r0, r1=autotrack(6,total.tracks)$r1)

#Color sets
pp <- getDefaultPlotParams(plot.type=4)
pp$leftmargin <- 0.2
kp <- plotKaryotype(plot.type=4, labels.plotter=NULL, ideogram.plotter=NULL, plot.params=pp)
kpAddChromosomeNames(kp, srt=45)
kpAddChromosomeSeparators(kp)

color.sets <- c( "2grays", "2blues", "blackgreen", "greengray", "brewer.set1",
                   "brewer.set2", "brewer.set3", "brewer.pastel1", "brewer.pastel2", "rainbow" )
total.tracks <- length(color.sets)
for(i in seq_len(length(color.sets))) {
    kpPoints(kp, points, y=0.5, col=colByChr(points, colors=color.sets[i]), cex=1, r0=autotrack(i,total.tracks)$r0, r1=autotrack(i,total.tracks)$r1)
    kpAddLabels(kp, labels=color.sets[i], cex=0.7, r0=autotrack(i,total.tracks)$r0, r1=autotrack(i,total.tracks)$r1)
}

Description

Given a set of data elements, return a color for each one based on whether they overlap a given set of regions. This might be useful, for example, to set a different color for data points overlapping a certain region of interest.

Usage

colByRegion(data, regions, colors=NULL, original.colors=NULL, default.col="black")

Arguments

Details

Given a set of data elements, return a color for each one based on whether they overlap a given set of regions. The colors might be different for each region and can be specified either in the regions object itself or in a separate colors parameter. If specified in colors, the values will be recycled as needed. Data points not in the specified region can take either a default color or keep their "original.color" if given. This is useful when using colByRegion to highlight data points as in kpPlotManhattan.

Value

A vector of colors

See Also

kpPoints, colByChr, toGRanges

Examples

data <- toGRanges("chr1", c(1e6*1:245), c(1e6*1:245)+10)
data$y <- rnorm(n = length(data), mean = 0.5, sd = 0.15)

regions <- toGRanges(c("chr1:10e6-20e6", "chr1:100e6-150e6"))
regions$col <- c("red", "blue")

kp <- plotKaryotype(chromosomes="chr1")
kpPoints(kp, data=data, r0=0, r1=0.2)
kpPoints(kp, data=data, r0=0.2, r1=0.4, col=colByRegion(data, regions = regions) )
kpText(kp, data=data, r0=0.4, r1=0.6, col=colByRegion(data, regions = regions), label="A", cex=0.5 )
kpBars(kp, data=data, y0=0, y1=data$y, r0=0.6, r1=0.8, border=colByRegion(data, regions = regions))
#It might not work wor objects where R expects a single color such as lines. Segments should be used instead
kpLines(kp, data=data, r0=0.8, r1=1, col=colByRegion(data, regions = regions) )


kp <- plotKaryotype(chromosomes="chr1")
kpPoints(kp, data=data, r0=0, r1=0.25)
kpPoints(kp, data=data, r0=0.25, r1=0.5, col=colByRegion(data, regions = regions, colors="green") )
kpText(kp, data=data, r0=0.5, r1=0.75, col=colByRegion(data, regions = regions, color=c("gray", "gold")), label="A", cex=0.5 )
kpBars(kp, data=data, y0=0, y1=data$y, r0=0.75, r1=1, border=colByRegion(data, regions = regions))

Description

Given a set of values, return a color for each of them based on their numeric value.

Usage

colByValue(value, colors, min=NULL, max=NULL)

Arguments

Details

A color ramp (similar to a gradient) will be built using the colors in the 'colors' parameter using colorRamp. Values will be normalized to [0,1] using 'min' and 'max' (if NULL, min(value) will be 0 and max(value) will be 1) and these values will be used to determine the color. It uses

Value

A vector of colors

Note

Alpha values (transparency) are also used in the color computation (see examples)

See Also

kpPoints, colByChr

Examples

colByValue(c(0,0.25,0.5,0.75,1), colors=c("red", "green"))
colByValue(c(0,0.25,0.5,0.75,1), colors=c("#00000000", "#00000011"))

data <- toGRanges("chr1", c(1e6*1:245), c(1e6*1:245)+10)
data$y <- rnorm(n = length(data), mean = 0.5, sd = 0.15)

kp <- plotKaryotype(chromosomes="chr1")
kpPoints(kp, data=data, r0=0, r1=0.3)
kpPoints(kp, data=data, r0=0.35, r1=0.65, col=colByValue(data$y, colors=c("black", "green")) )
kpPoints(kp, data=data, r0=0.7, r1=1, col=colByValue(data$y, colors=c("black", "green"), min=0.4, max=0.6))

kp <- plotKaryotype(chromosomes="chr1")
kpPoints(kp, data=data, r0=0, r1=0.3, col=colByValue(data$y, colors=c("#00000000", "#000000FF")))
kpPoints(kp, data=data, r0=0.35, r1=0.65, col=colByValue(data$y, colors=c("black", "orange", "green")) )
kpPoints(kp, data=data, r0=0.7, r1=1, col=colByValue(data$y, colors=c("red", "#00000022","#00000022", "green"),min=0.4, max=0.6))

Description

Given a color, return a darker one

Usage

darker(col, amount=150)

Arguments

Details

Very simple utility function to create darker colors. Given a color, it transforms it to rgb space, adds a set amount to all chanels and transforms it back to a color.

Value

A darker color

See Also

lighter

Examples

darker("red")
darker("#333333")
darker(c("red", 3, "#FF00FF"))

Description

Given a list, select just only the valid.elements from each member. Also works with vectors instead of lists

Usage

filterParams(p, valid.elements, orig.length)

Arguments

Details

This function is used in filtering the graphical parameters when plotting only a part of the genome. For each element of the list, if it has the exact specified length, filters it using the 'valid.elements' parameter.

Value

p with some members filtered

Examples

a <- 1:10
b <- 3:5
c <- 2

filterParams(list(a,b,c), c(rep(TRUE,5), rep(FALSE,5)), 10)
filterParams(a, c(rep(TRUE,5), rep(FALSE,5)), 10)

Description

Finds the intersections of a data line with a given threshold

Usage

findIntersections(data, thr)

Arguments

Details

Given a GRanges with an mcol with name "y" representing the values. This function will return a GRanges with the points intersecting a specific value "thr".

Value

A GRanges representing the intersection points between the data line and the threshold. It will return an empty GRanges if the line does not intersect the threshold.

Note

Important: It will only return the intersection points where the line crosses the threshold but not if a data point lies exactly at the threshold.

Examples

d <- toGRanges(c("1:1-1", "1:5-5", "1:15-15"))
d$y <- c(-2, 3, 1)
 
findIntersections(d, 1.5)  
findIntersections(d, 0)  
findIntersections(d, 5)

Description

Return the regions where the chromosome names should be placed

Usage

getChromosomeNamesBoundingBox(karyoplot)

Arguments

Details

Given a KaryoPlot object, return the regions where the chromosome labels should be placed. The positions will depend on the plot type used.

Value

Returns a list with four elements (x0, x1, y0 and y1), each of them a named vector of integers with one coordinatefor every chromosome in the plot.

Note

In general, this function is automatically called by karyoploteR and the user never needs to call it.

See Also

plotKaryotype, kpAddChromosomeNames

Examples

kp <- plotKaryotype()
bb <- getChromosomeNamesBoundingBox(kp)

Description

Return a structure with the color schemas included in karyoploteR

Usage

getColorSchemas()

Value

A list with the color schemas included in karyoploteR for cytobands, variants, horizons...

Examples

getColorSchemas()

Description

Returns a named character vector with the colors of associated with the cytoband names

Usage

getCytobandColors(color.table=NULL, color.schema=c("circos", "biovizbase", "only.centromeres"))

Arguments

Details

The function returns a named character vector with the colors of associated with the cytoband names. Two color schemas are available: circos (which copies the colors used by Circos) and biovizbase (that gets the cytoband colors from the biovizBase Bioconductor package). If a color.table is given, it is returned untouched.

Value

a named character vector with the colors associated to each cytoband name

See Also

plotKaryotype, kpAddCytobands

Examples

getCytobandColors()
getCytobandColors(color.schema="biovizbase")

Description

Get the cytobands of the specified genome.

Usage

getCytobands(genome="hg19", use.cache=TRUE)

Arguments

Details

It returns GRanges object with the cytobands of the specified genome. The cytobands for some organisms and genome versions have been pre-downloaded from UCSC and included in the karyoploteR package. For any other genome, getCytobands will use rtracklayer to try to fetch the cytoBandIdeo table from UCSC. If for some reason it is not possible to retrieve the cytobands, it will return an empty GRanges object. Setting the parameter use.cache to FALSE, the data included in the package will be ignored and the cytobands will be downloaded from UCSC.

The genomes (and versions) with pre-downloaded cytobands are: hg18, hg19, hg38, mm9, mm10, mm39, rn5, rn6, rn7, susScr11, bosTau9, bosTau8, equCab3, equCab2, panTro6, panTro5, rheMac10, danRer10, danRer11, xenTro10, dm3, dm6, ce6, ce10, ce11, sacCer2, sacCer3

Value

It returns a GenomicRanges object with the cytobands of the specified genome. If no cytobands are available for any reason, an empty GRanges is returned.

Note

This function is memoised (cached) using the memoise package. To empty the cache, use forget(getCytobands)

See Also

plotKaryotype

Examples

#get the cytobands for hg19 (using the data included in the package)
cyto <- getCytobands("hg19")


#get the cytobands for Drosophila Melanogaster
cyto <- getCytobands("dm6")

Description

Return the bounding box of a data panel in plot coordinates

Usage

getDataPanelBoundingBox(karyoplot, data.panel)

Arguments

Details

Given a KaryoPlot object and a data.panel name, return the region where the data panel is placed. The returned values are in plot coordinates, that is, the coord.change.function has been applied.

Value

Returns a list with four elements (x0, x1, y0 and y1), each of them an integer with the plot coordinates for the data.panel

Note

A user is not expected to need this function. It is mainly used by plotting functions, specially when clipping the plot in a zoomed region.

See Also

plotKaryotype, kpDataBackground

Examples

kp <- plotKaryotype(plot.type=2)
dp1 <- getDataPanelBoundingBox(kp, 1)

Description

Returns the default parameters for the given plot.type

Usage

getDefaultPlotParams(plot.type)

Arguments

Details

Given a plot.type, this function returns a list suitable as a valid plot.params object. The user can then proceed to change the parameter values as needed and supply the modified list to the plotKaryotype function.#'

Value

A valid plot.params object with the default values for the plotting parameters and ready to be used in the plotKaryotype

See Also

plotKaryotype

Examples

pp <- getDefaultPlotParams(plot.type=2)
pp

#Change the ideogramheight param to create thicker ideograms 
pp$ideogramheight <- 150

plotKaryotype(genome="hg19", plot.type=2, plot.params=pp)

Description

Return the regions where the chromosome names should be placed

Usage

getMainTitleBoundingBox(karyoplot)

Arguments

Details

Given a KaryoPlot object, return the regions where the main plot should be placed. The position will depend on the plot type used.

Value

Returns a list with four elements (x0, x1, y0 and y1), each of them an integer with the coordinates for the main title

Note

In general, this function is automatically called by karyoploteR and the user never needs to call it.

See Also

plotKaryotype, kpAddMainTitle

Examples

kp <- plotKaryotype()
bb <- getMainTitleBoundingBox(kp)

Description

Returns the size of character strings in bases and r's

Usage

getTextSize(karyoplot, labels, cex=1, data.panel="1")

Arguments

Details

Small utility function to get the size of text labels in usable units for karyoploteR: bases for the width and r's for the height. The r units are the ones passed to r0 and r1 and take into account that a data panel has always total height of 1 r (from r0=0 to r1=1)

Value

Returns a list with two elements: width and height. Each of them is a numeric vector of the same length as "labels" with the width in bases of each label and the height in r units of each label.

Examples

pp <- getDefaultPlotParams(plot.type=2)
pp$data2height <- 50

kp <- plotKaryotype(chromosomes="chr1", plot.type=2, plot.params=pp)
 
label <- "Looooooong label"
kpText(kp, chr="chr1", x=70e6, y=0.5, labels=label)
text.size <- getTextSize(kp, labels=label)
kpRect(kp, chr="chr1", x0=70e6-text.size$width/2, x1=70e6+text.size$width/2,
           y0=0.5-text.size$height/2, y1=0.5+text.size$height/2)
 
label <- "SHORT"
text.size <- getTextSize(kp, labels=label, cex=3)
kpRect(kp, chr="chr1", x0=170e6-text.size$width/2, x1=170e6+text.size$width/2,
           y0=0.2-text.size$height/2, y1=0.2+text.size$height/2, col="gold")
kpText(kp, chr="chr1", x=170e6, y=0.2, labels=label, cex=3)
    
label <- c("two_labels", "in a small data.panel=2")
kpText(kp, chr="chr1", x=c(100e6, 170e6), y=c(0.4, 0.2), labels=label, cex=0.6, data.panel=2)
text.size <- getTextSize(kp, labels=label, cex=0.6, data.panel=2)
kpRect(kp, chr="chr1", x0=c(100e6, 170e6)-text.size$width/2, x1=c(100e6, 170e6)+text.size$width/2,
           y0=c(0.4, 0.2)-text.size$height/2, y1=c(0.4, 0.2)+text.size$height/2, data.panel=2)

Description

Given the reference and alternative for a set of variants, assigns a color to each of them

Usage

getVariantsColors(ref, alt, color.table=NULL, color.schema=c("cell21breast"))

Arguments

Details

The function creates an nucleotide substitution identifier with for each variant and uses it to query the color.table lookup table. If color.table is NULL, a color.table based in the selected color.schema is used. All unkwonwn nucleotide substitutions are assigned a gray color. Color table needs to have entries for C>A, C>G, C>T, T>A, T>C and T>G (and optionally "others"), since other changes can be reverse complemented to these.

Value

a named character vector with the colors associated to each variant

See Also

plotKaryotype, kpPlotRainfall

Examples

ref <- c("A", "A", "C", "T", "G", "A")
alt <- c("G", "C", "T", "A", "A", "-")
getVariantsColors(ref, alt)

col.table <- c("C>A"="#FF0000", "C>G"="#000000", "C>T"="#00FF00", "T>A"="#0000FF", "T>C"="#BB00BB", "T>G"="#00BBBB", "other"="#888888")
getVariantsColors(ref, alt, col.table)

Description

Returns the color structure needed by kpPlotHorizon

Usage

horizonColors(col, num.parts)

Arguments

Details

This function transforms an array of colors into a list of colors **internally** needed by kpPlotHorizon: a list with two elements, "neg" and "pos", each an array of colors of length num.parts. If col is a character of length one, it is interpreted as the name of a color scheme.

horizonColors(col, num.parts)

Value

A list with 2 elements, pos and neg, each with num.parts colors

Examples

horizonColors("redblue6", 3)
horizonColors("redblue6", 6)
horizonColors("bluegold3", 2)
horizonColors(c("red", "blue"), 3)
horizonColors(c("red", "#FFFFFF00", "blue"), 3)

Description

Test if something is a valid color

Usage

is.color(x)

Arguments

Details

This function tests if something is a valid color. Returns TRUE or FALSE. The function is vectorised.

Value

TRUE is x is a valid color, FALSE otherwise

Examples

is.color("red")
is.color("#333333")
is.color(NA)
is.color(NULL)
is.color("not_a_color")
is.color(3)

is.color(c("not_a_color", "red", 3, "#FF0000"))

Description

This is the KaryoploteR version of the abline function to add horizontal or vertical lines to the plot.

Usage

kpAbline(karyoplot, chr=NULL, h=NULL, v=NULL, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL,  clipping=TRUE, ...)

Arguments

Details

As with all other base-inspired low-level plotting functions in karyoploteR, the function has been designed to accept mostly the same parameters as the base one (see the package vignette for more information). In this case, however, the interface has been reduced and it is only possible to plot vertical and horizontal lines and it's not possible to provide an intercept and slope. In addition, the function accepts graphical parameters that are valid for the base function segments.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpSegments, kpLines

Examples

set.seed(1000)
data.points <- sort(createRandomRegions(nregions=1000, mask=NA))
mcols(data.points) <- data.frame(y=rnorm(1000, mean = 0.5, sd = 0.1))

kp <- plotKaryotype("hg19", plot.type=1, chromosomes=c("chr1", "chr2"))
kpDataBackground(kp, data.panel=1)

kpPoints(kp, data=data.points, pch=".", col="#2222FF", cex=3)

#Add horizontal lines at mean
kpAbline(kp, h=0.5, col="red")

#and at the 1 sd
kpAbline(kp, h=c(0.4, 0.6), col="orange", lwd=0.5)
#and 2 sd's
kpAbline(kp, h=c(0.3, 0.7), col="orange", lwd=0.5, lty=2)

#And add two vertical lines at specific chromosomal locations
kpAbline(kp, v=c(67000000, 190000000), chr="chr1")

Description

Plots the base numbers along the chromosome ideograms

Usage

kpAddBaseNumbers(karyoplot, tick.dist=20000000, tick.len=5, units="auto", add.units=FALSE, digits=2, minor.ticks=TRUE, minor.tick.dist=5000000, minor.tick.len=2,  cex=0.5, tick.col=NULL, minor.tick.col=NULL, clipping=TRUE, ...)

Arguments

Details

This function can be used to add the base numbers scale to the chromosome ideograms. The base numbers and ticks will be drawn next to the ideograms and not on a separate independent x axis. It is possible to control the number and position of the tick marks and labels

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype

Examples

kp <- plotKaryotype()
kpAddBaseNumbers(kp)

kp <- plotKaryotype(chromosomes="chr17")
kpAddBaseNumbers(kp, tick.dist=10000000, minor.tick.dist=1000000)

Description

Plots the chromosome names in the karyoplot

Usage

kpAddChromosomeNames(karyoplot, chr.names=NULL, xoffset=0, yoffset=0, ...)

Arguments

Details

Given a KaryoPlot object, plot the names of the depicted chromosomes. This function is usually automatically called by plotKaryotype unless labels.plotter is NULL.

Value

invisibly returns the given karyoplot object

See Also

plotKaryotype, getChromosomeNamesBoundingBox

Examples

kp <- plotKaryotype(labels.plotter = NULL)
kpAddChromosomeNames(kp, col="red", srt=30)

Description

Plots between the chromosomes

Usage

kpAddChromosomeSeparators(karyoplot, col="gray", lty=3, data.panel="all", ...)

Arguments

Details

Depending on the plot type it will draw vertical lines (if all chromosomes are in a one line (3,4,5,7)) or horizontal lines (1,2,6)

By default the lines will occupy the whole chromsome extent (data.panel="all") but using the data.panel parameter it can be tuned.

Value

invisibly returns the given karyoplot object

See Also

plotKaryotype

Examples

kp <- plotKaryotype(plot.type=4)
kpAddChromosomeSeparators(kp)

kp <- plotKaryotype(plot.type=5, ideogram.plotter=NULL)
kpAddChromosomeSeparators(kp)

kp <- plotKaryotype(plot.type=2)
kpAddChromosomeSeparators(kp, col="red")

Description

Add color rectangles next to the data panels. Ideal to identify the data in the plot

Usage

kpAddColorRect(karyoplot, col="gray", rect.width=0.02, rect.margin=0.01,  side="left", y0=0, y1=1, r0=NULL, r1=NULL, data.panel=1, border=NA, ...)

Arguments

Details

Given a KaryoPlot object, plot colored rectangles on the side of the data panels to help identify the different samples or types of data plotted

Value

invisibly returns the given karyoplot object

See Also

plotKaryotype, autotrack

Examples

num.samples <- 10
samples.metadata <- data.frame(stage=c("I", "I", "I", "III", "IV", "III", "II", "IV", "IV", "IV"),
                                metastasis=c(0,0,0,0,1,0,0,0,1,0),
                                subtype=c("A", "A", "B", "B", "A", "B", "B", "B", "A", "B"))

kp <- plotKaryotype(plot.type=4)
for(i in 1:num.samples) {
  #metastasis
  kpAddColorRect(kp, col = colByCategory(samples.metadata$metastasis, color=c("white", "black"))[i],
                 rect.margin = 0.01, rect.width = 0.01, r0=autotrack(i, num.samples))
  #stage
  kpAddColorRect(kp, 
    col = colByCategory(samples.metadata$stage, colors=c("I"="plum1", "II"="hotpink", "III"="orange", "IV"="red2"))[i],
    rect.margin = 0.021, rect.width = 0.01, r0=autotrack(i, num.samples))
  #subtype
  kpAddColorRect(kp, 
                 col = colByCategory(samples.metadata$subtype, colors=c("dodgerblue", "gold"))[i],
                 rect.margin = 0.032, rect.width = 0.01, r0=autotrack(i, num.samples))
}

Description

Plots the base numbers along the chromosome ideograms

Usage

kpAddCytobandLabels(karyoplot, cex=0.5, force.all=FALSE, clipping=TRUE, ...)

Arguments

Details

This function can be used to add labels idenfifying the cytobands. It gets the labels from the cytobands information stored in the karyoplot object and it will only plot the labels that fit inside the available space. This means than in some cases (such as when plotting a complete genome with default parameters) it is possible that no labels at all are added.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype

Examples

kp <- plotKaryotype()
kpAddBaseNumbers(kp)
kpAddCytobandLabels(kp)

kp <- plotKaryotype(chromosomes="chr17")
kpAddBaseNumbers(kp, tick.dist=10000000, minor.tick.dist=1000000)
kpAddCytobandLabels(kp)

Description

Plots the chromosome cytobands in a karyoplot

Usage

kpAddCytobands(karyoplot, color.table=NULL, color.schema=c("circos", "biovizbase", "only.centromeres"), clipping=TRUE, ...)

Arguments

Details

Plots the cytobands representing the chromosome structure in a karyoplot. It extracts the cytobands from the karyoplot object it recieves as a parameter. It is possible to specify the colors used to plot the cytobands.

Value

invisibly returns the given karyoplot object

Note

In general, this function is automatically called by plotKaryotype and the user never nees to call it.

See Also

plotKaryotype, getCytobandColors, kpAddBaseNumbers, kpAddCytobandLabels

Examples

kp <- plotKaryotype(ideogram.plotter = NULL)
kpAddCytobands(kp)

Description

Plots the chromosome cytobands in a karyoplot as a line

Usage

kpAddCytobandsAsLine(karyoplot, color.table=NULL, color.schema='only.centromeres', lwd=3, lend=1, clipping=TRUE, ...)

Arguments

Details

Plots the cytobands representing the chromosome structure in a karyoplot. It extracts the cytobands from the karyoplot object it recieves as a parameter. It is possible to specify the colors used to plot the cytobands. In contrast to kpAddCytobands it represents the chromosomes as a thin line

Value

invisibly returns the given karyoplot object

Note

In general, this function is automatically called by plotKaryotype and the user never needs to call it.

See Also

plotKaryotype, getCytobandColors, kpAddBaseNumbers, kpAddCytobandLabels

Examples

kp <- plotKaryotype(ideogram.plotter = NULL)
kpAddCytobandsAsLine(kp)
 
kp <- plotKaryotype(ideogram.plotter = NULL, plot.type=2)
kpAddCytobandsAsLine(kp)

Description

Add labels to identify the data in the plot

Usage

kpAddLabels(karyoplot, labels, label.margin=0.01,  side="left", pos=NULL, offset=0, r0=NULL, r1=NULL, data.panel=1, ...)

Arguments

Details

Given a KaryoPlot object, plot labels on the side of the data panels to help identify the different types of data plotted

Value

invisibly returns the given karyoplot object

See Also

plotKaryotype

Examples

plot.params <- getDefaultPlotParams(plot.type=2)
plot.params$leftmargin <- 0.2
plot.params$rightmargin <- 0.2

#In standard whole karyotypes, labels are drawn for all chromosomes

kp <- plotKaryotype("hg19", chromosomes=c("chr1", "chr2"), plot.type=2, plot.params = plot.params)
#data panel 1
kpDataBackground(kp, r0=0, r1=0.5, col="#FFDDDD")
kpDataBackground(kp, r0=0.5, r1=1, col="#DDFFDD")
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=3, cex=0.8)
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6)
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6)
#data panel 2
kpDataBackground(kp, col="#DDDDFF", data.panel = 2)
kpAddLabels(kp, "BLUE", data.panel=2)

#Plot on the right
#data panel 1
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=1, cex=0.8, side="right")
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6, side="right")
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6, side="right")
 
 
 
#In karyotypes with all chromosomes in a single line, 
#labels are added on the first (side="left") or last (side="right") chromosome

kp <- plotKaryotype("hg19", chromosomes=c("chr1", "chr2", "chr3"), plot.type=3, plot.params = plot.params)
#data panel 1
kpDataBackground(kp, r0=0, r1=0.5, col="#FFDDDD")
kpDataBackground(kp, r0=0.5, r1=1, col="#DDFFDD")
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=3, cex=0.8)
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6)
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6)
#data panel 2
kpDataBackground(kp, col="#DDDDFF", data.panel = 2)
kpAddLabels(kp, "BLUE", data.panel=2)

#Plot on the right
#data panel 1
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=1, cex=0.8, side="right")
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6, side="right")
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6, side="right")



#In Zoomed regions, they are placed at the correct position too
kp <- plotKaryotype("hg19", zoom="chr1:20000000-40000000", plot.type=2, plot.params = plot.params)
kpAddBaseNumbers(kp, tick.dist=5000000, add.units=TRUE)
#data panel 1
kpDataBackground(kp, r0=0, r1=0.5, col="#FFDDDD")
kpDataBackground(kp, r0=0.5, r1=1, col="#DDFFDD")
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=3, cex=0.8)
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6)
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6)
#data panel 2
kpDataBackground(kp, col="#DDDDFF", data.panel = 2)
kpAddLabels(kp, "BLUE", data.panel=2)

#Plot on the right
#data panel 1
kpAddLabels(kp, "Everything", label.margin = 0.12, srt=90, pos=1, cex=0.8, side="right")
kpAddLabels(kp, "Red", r0=0, r1=0.5, cex=0.6, side="right")
kpAddLabels(kp, "Green", r0=0.5, r1=1, cex=0.6, side="right")

Description

Plots the chromosome names in the karyoplot

Usage

kpAddMainTitle(karyoplot, main=NULL, ...)

Arguments

Details

Given a KaryoPlot object and a character string, plot the character strings as the main title of the plot. This function is usually automatically called by plotKaryotype unless.

Value

invisibly returns the given karyoplot object

See Also

plotKaryotype, getMainTitleBoundingBox

Examples

kp <- plotKaryotype(labels.plotter = NULL)
kpAddMainTitle(kp, col="red", srt=30)

Description

Plots a line joining the data points along the genome and fills the area below the line.

Usage

kpArea(karyoplot, data=NULL, chr=NULL, x=NULL, y=NULL, base.y=0, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, col=NULL, border=NULL, clipping=TRUE, ...)

Arguments

Details

This is a karyoploteR low-level plotting functions. Given a set of positions on the genome (chromosome and base) and a value (y) for each of them, it plots a line joining them and shades the area below them. Data can be provided via a GRanges object (data), independent parameters for chr, x and y or a combination of both. A number of parameters can be used to define exactly where and how the line and area are drawn. In addition, via the ellipsis operator (...), kpArea accepts any parameter valid for lines and polygon (e.g. lwd, lty, col, density...) The lines are drawn in a per chromosome basis, so it is not possible to draw lines encompassing more than one chromosome.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpLines, kpText, kpPlotRibbon

Examples

set.seed(1000)
data.points <- sort(createRandomRegions(nregions=500, mask=NA))
mcols(data.points) <- data.frame(y=runif(500, min=0, max=1))

kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))
  kpDataBackground(kp, data.panel=1)
  kpDataBackground(kp, data.panel=2)

  kpArea(kp, data=data.points)
  kpArea(kp, data=data.points, col="lightgray", border="red", lty=2, r0=0, r1=0.5)
  kpArea(kp, data=data.points, border="red", data.panel=2, r0=0, r1=0.5)
  kpArea(kp, data=data.points, border="blue", data.panel=2, r0=0, r1=0.5, base.y=1)

  kpArea(kp, data=data.points, border="gold", data.panel=2, r0=0.5, r1=1, base.y=0.5)

Description

Plots segments at the specified genomic positions.

Usage

kpArrows(karyoplot, data=NULL, chr=NULL, x0=NULL, x1=NULL, y0=NULL, y1=NULL, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, clipping=TRUE, ...)

Arguments

Details

This is one of the functions from karyoploteR implementing the adaptation to the genome context of basic plot functions from R base graphics. Given a set of positions on the genome (chromosome, x0 and x1) and values (y0 and y1) for each of them, it plots arrows going from (x0, y0) to (x1, y1). Data can be provided via a GRanges object (data), independent parameters for chr, x0, x1, y0 and y1, or a combination of both. A number of parameters can be used to define exactly where and how the arrows are drawn. In addition, via the ellipsis operator (...), kpSegments accepts any parameter valid for segments (e.g. code, lwd, lty, col, ...)

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpRect, kpPoints,

kpPlotRegions

Examples

set.seed(1000)
data.points <- sort(createRandomRegions(nregions=500, length.mean=2000000, mask=NA))
y <- runif(500, min=0, max=0.8)
mcols(data.points) <- data.frame(y0=y, y1=y+0.2)

kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))
  kpDataBackground(kp, data.panel=1)
  kpDataBackground(kp, data.panel=2)

  kpArrows(kp, data=data.points, col="black", lwd=2, length=0.04)
  
  kpArrows(kp, data=data.points, y0=0, y1=1,  r0=0.2, r1=0.8, col="lightblue", data.panel=2)

Description

Plot axis at the sides of the data panels

Usage

kpAxis(karyoplot, ymin=NULL, ymax=NULL, r0=NULL, r1=NULL, side=1, numticks=3, labels=NULL, tick.pos=NULL, tick.len=NULL, label.margin=NULL, data.panel=1, text.col="black", col="black", chromosomes="auto", ...)

Arguments

Details

kpAxis plots axis at the sides of the data panels. It is possible to control the number of ticks and their labels, the placement of the plots and whether they span the whole data panel or just part of it. To do that they use the same placement parameters used by other karyoploteR functions (r0 and r1). This function does not have a chr option: axis are always plotted for all chromosomes.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpDataBackground, kpAbline

Examples

kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))

#Prepare data panel 1
kpDataBackground(kp, data.panel=1)
kpAxis(kp, data.panel = 1)
kpAxis(kp, data.panel = 1, ymin = 0, ymax=10, numticks = 11, side = 2, cex = 0.4, col="red")

#Prepare data panel 2
#Data panel 2 is conceptually split into two parts and the second part is "inverted"
kpDataBackground(kp, data.panel=2, r0 = 0, r1 = 0.45, color = "#EEEEFF")
kpAxis(kp, data.panel = 2, r0=0, r1=0.45, ymin = 0, ymax = 1, cex=0.5, 
           tick.pos = c(0.3, 0.5, 0.7), labels = c("-1 sd", "mean", "+1 sd"))
kpAxis(kp, data.panel = 2, r0=0, r1=0.45, ymin = 0, ymax = 1, cex=0.5, side=2)

kpDataBackground(kp, data.panel=2, r0 = 0.55, r1 = 1, color = "#EEFFEE")
kpAxis(kp, data.panel = 2, r0=1, r1=0.55, ymin = 0, ymax = 1, side=1, cex=0.5)
kpAxis(kp, data.panel = 2, r0=1, r1=0.55, ymin = 0, ymax = 1, side=2, cex=0.5)


#Customizing the axis appearance
pp <- getDefaultPlotParams(plot.type=4)
pp$leftmargin <- 0.2
pp$rightmargin <- 0.2
kp <- plotKaryotype("hg19", plot.type=4, chromosomes=c("chr1", "chr2"), plot.params=pp)

#Prepare data panel 1
kpDataBackground(kp, data.panel=1)
kpAxis(kp, data.panel = 1, text.col="red", cex=1.6, srt=45)
kpAxis(kp, data.panel = 1, ymin = 0, ymax=10, numticks = 11, side = 2, 
       cex = 0.7, col="red", text.col="gold", tick.len=30e6, )

Description

Plot bars along the genome

Usage

kpBars(karyoplot, data=NULL, chr=NULL, x0=NULL, x1=x0, y1=NULL, y0=NULL, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, clipping=TRUE, ...)

Arguments

Details

kpBars plots bars (rectangles) along the genome. It is very similar to kpRect except that if y0 is missing, it's automatically set to ymin so all bars start from the base of the plotting region.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpRect, kpLines

Examples

set.seed(1000)

data <- toGRanges(data.frame(chr="chr1", start=10000000*(0:23), end=10000000*(1:24)))
y1 <- ((sin(start(data)) + rnorm(n=24, mean=0, sd=0.1))/5)+0.5
y0 <- y1 - rnorm(n=24, mean = 0, sd = 0.15)
 
kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))

#We can specify all data values separately. If missing y0, it defaults to ymin
kpBars(kp, chr=as.character(seqnames(data)), x0=start(data), x1=end(data), y1=y1,
       col="#FFBBBB", border="#EEAAAA")
kpLines(kp, data=data, y=y1, col="red")

#or we can provide all data into a single GRanges object
mcols(data) <- data.frame(y0=y0, y1=y1)
kpBars(kp, data[data$y0>data$y1], col="orange", border="orange", data.panel=2)
kpBars(kp, data[data$y0<=data$y1], col="purple", border="purple", data.panel=2)

kpLines(kp, data, y=data$y1, data.panel=2, col="red")
kpLines(kp, data, y=data$y0, data.panel=2, col="blue")

kpAxis(kp, data.panel = 1, cex=0.8, numticks = 5, col="#777777")
kpAxis(kp, data.panel = 2, cex=0.8, numticks = 5, col="#777777")

Description

Draws a solid rectangle delimiting the plotting area

Usage

kpDataBackground(karyoplot, r0=NULL, r1=NULL, data.panel=1, color="gray90", clipping=TRUE, ...)

Arguments

Details

This function is used to add a background color to delimit the plotting area. It can either delimit the whole plotting area or part of it so different data plotting regions can be seen.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpAxis

Examples

kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))

#Prepare data panel 1
kpDataBackground(kp, data.panel=1)
kpAxis(kp, data.panel = 1)
kpAxis(kp, data.panel = 1, ymin = 0, ymax=10, numticks = 11, side = 2, cex = 0.4, col="red")

#Prepare data panel 2
#Data panel 2 is conceptually split into two parts and the second part is "inverted"
kpDataBackground(kp, data.panel=2, r0 = 0, r1 = 0.45, color = "#EEEEFF")
kpAxis(kp, data.panel = 2, r0=0, r1=0.45, ymin = 0, ymax = 1, cex=0.5, 
       tick.pos = c(0.3, 0.5, 0.7), labels = c("-1 sd", "mean", "+1 sd"))
kpAxis(kp, data.panel = 2, r0=0, r1=0.45, ymin = 0, ymax = 1, cex=0.5, side=2)

kpDataBackground(kp, data.panel=2, r0 = 0.55, r1 = 1, color = "#EEFFEE")
kpAxis(kp, data.panel = 2, r0=1, r1=0.55, ymin = 0, ymax = 1, side=1, cex=0.5)
kpAxis(kp, data.panel = 2, r0=1, r1=0.55, ymin = 0, ymax = 1, side=2, cex=0.5)

Description

Plots the given data as a heatmap along the genome

Usage

kpHeatmap(karyoplot, data=NULL, chr=NULL, x0=NULL, x1=x0, y=NULL, ymax=NULL, ymin=NULL, r0=NULL, r1=NULL, data.panel=1, colors=c("blue", "white", "yellow"), clipping=TRUE, ...)

Arguments

Details

Given regions of the genome with a start, end and a value, draws a heatmap-like representation, with the color of the region determined by its value. It is important to note that kpHeatmap will not extend the regions in any way, so if regions are not contiguous, they will appear as a series of rectangles and not as a continuous plot.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpRect, kpLines

Examples

dd <- toGRanges(data.frame(chr="chr1", start=4980000*(0:49), end=4980000*(1:50)))
y <- sin(x=c(1:length(dd))/2)

kp <- plotKaryotype("hg19", plot.type=1, chromosomes=c("chr1", "chr2"))

kpLines(kp, dd, y=y, r0=0.4, r1=0.6, ymin=-1, ymax=1)
kpAxis(kp, r0=0.4, r1=0.6, ymin=-1, ymax=1, cex=0.5)

kpHeatmap(kp, dd, y=y, colors = c("red", "black", "green"), r0=0, r1=0.2)
kpHeatmap(kp, dd, y=y, colors = c("green", "black", "red"), r0=0.2, r1=0.4)

#or we can provide all data into a single GRanges object
mcols(dd) <- data.frame(y=y)

kpHeatmap(kp, dd, r0=0.6, r1=0.8)
#non-contiguous regions appear as solitary rectangles
kpHeatmap(kp, sample(x = dd, 10), r0=0.8, r1=1, color=c("orange", "black", "purple", "green"))

Description

Plots a line joining the data points along the genome.

Usage

kpLines(karyoplot, data=NULL, chr=NULL, x=NULL, y=NULL, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, clipping=TRUE, ...)

Arguments

Details

This is one of the functions from karyoploteR implementing the adaptation to the genome context of basic plot functions from R base graphics. Given a set of positions on the genome (chromosome and base) and a value (y) for each of them, it plots a line joining them. Data can be provided via a GRanges object (data), independent parameters for chr, x and y or a combination of both. A number of parameters can be used to define exactly where and how the lines are drawn. In addition, via the ellipsis operator (...), kpLines accepts any parameter valid for lines (e.g. lwd, lty, col, ...) The lines are drawn in a per chromosome basis, so it is not possible to draw lines encompassing more than one chromosome.

Value

Returns the original karyoplot object, unchanged.

See Also

plotKaryotype, kpLines, kpText, kpPlotRegions

Examples

set.seed(1000)
data.points <- sort(createRandomRegions(nregions=500, mask=NA))
mcols(data.points) <- data.frame(y=runif(500, min=0, max=1))

kp <- plotKaryotype("hg19", plot.type=2, chromosomes=c("chr1", "chr2"))
  kpDataBackground(kp, data.panel=1)
  kpDataBackground(kp, data.panel=2)

  kpLines(kp, data=data.points, col="red")

  #Three ways of specifying the exact same data.points
  kpPoints(kp, data=data.points)
  kpPoints(kp, data=data.points, y=data.points$y, pch=16, col="#CCCCFF", cex=0.6)
  kpPoints(kp, chr=as.character(seqnames(data.points)), 
           x=(start(data.points)+end(data.points))/2, y=data.points$y, pch=".",
           col="black", cex=1)

  #plotting in the data.panel=2 and using r0 and r1, ymin and ymax
  kpLines(kp, data=data.points, col="red", r0=0, r1=0.3, data.panel=2)
  kpPoints(kp, data=data.points, r0=0, r1=0.3, data.panel=2, pch=".", cex=3)

  kpLines(kp, data=data.points, col="blue", r0=0.4, r1=0.7, data.panel=2)
  kpLines(kp, data=data.points, col="blue", y=-1*(data.points$y), 
          ymin=-1, ymax=0, r0=0.7, r1=1, data.panel=2)
  #It is also possible to "flip" the data by giving an r0 > r1
  kpPoints(kp, data=data.points, col="red", y=(data.points$y), 
           r0=1, r1=0.7, data.panel=2, pch=".", cex=2)

Description

Plots the coverage of a BAM file along the genome

Usage

kpPlotBAMCoverage(karyoplot, data=NULL, max.valid.region.size=1e6, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, col=NULL, border=NA, clipping=TRUE,...)

Arguments

Details

kpPlotBAMCoverage plots the read coverage of a BAM file, that is, the number of reads overlapping each position. It uses the bamsignals package to efficiently access the BAM file. The BAM file must be indexed. This function is only recommended when plotting small parts of the genome. For larger plots consider using kpPlotBAMDensity.

There's more information at the https://bernatgel.github.io/karyoploter_tutorial/karyoploteR tutorial.

Value

Returns the original karyoplot object with the data computed (max.coverage) stored at karyoplot$latest.plot

Note

Since the plotting the exact coverage for large regions of the genome may be unfeasable, it includes a safety mechanism causing it to raise a warning and do nothing if the region is larger than a threshold specified by max.valid.region.size.

See Also

kpPlotBAMDensity, kpPlotCoverage

Examples

library(pasillaBamSubset) #A package with 2 example bam files
un1.bam.file <- untreated1_chr4() # get the name of the first bam
un3.bam.file <- untreated3_chr4() #and the name of the second

kp <- plotKaryotype(genome="dm6", chromosomes="chr4") #The pasilla data comes from drosophila
kp <- kpAddBaseNumbers(kp, tick.dist = 1e5)
kp <- kpPlotBAMCoverage(kp, data = un1.bam.file) #Warning and does not plot. region too large.
kp <- kpPlotBAMCoverage(kp, data = un1.bam.file, max.valid.region.size=2000000)

#Use zoom to plot a smaller region to see the coverage with more detail
kp <- plotKaryotype(genome="dm6", zoom=toGRanges("chr4", 340000, 350000))
kp <- kpAddBaseNumbers(kp, tick.dist = 1e3)
kp <- kpPlotBAMCoverage(kp, data = un1.bam.file)


#Change the colors and borders and compare  two bams
kp <- plotKaryotype(genome="dm6", zoom=toGRanges("chr4", 340000, 350000))
kp <- kpAddBaseNumbers(kp, tick.dist = 1e3)
kp <- kpPlotBAMCoverage(kp, data = un1.bam.file, r0=0.5, r1=1, border="orange")
kp <- kpPlotBAMCoverage(kp, data = un3.bam.file, r0=0.5, r1=0, border="darkgreen") #r1 < r0 will flip the plot
kpAbline(kp, h=0.5, col="darkgray")

Description

Plots the density of features along the genome

Usage

kpPlotBAMDensity(karyoplot, data=NULL, window.size=1e6, normalize=FALSE, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, col="gray80", border=NA,  clipping=TRUE, ...)

Arguments

Details

kpPlotBAMDensity plots the read density of a BAM file. It does not plot the coverage but the read density as the number of reads overlapping a every window. It uses Rsamtools to efficiently access the BAM file. The BAM file must be indexed.

There's more information at the https://bernatgel.github.io/karyoploter_tutorial/karyoploteR tutorial.

Value

Returns the original karyoplot object with the data computed (windows and density) stored at karyoplot$latest.plot

See Also

plotKaryotype, kpPlotRibbon, kpPlotCoverage

Examples

library(pasillaBamSubset) #A package with 2 example bam files
un1.bam.file <- untreated1_chr4() # get the name of the first bam
un3.bam.file <- untreated3_chr4() #and the name of the second

window.size <- 1e4 #compute the density with 10kb windows

kp <- plotKaryotype(genome="dm6", chromosomes="chr4") #The pasilla data comes from drosophila
kp <- kpAddBaseNumbers(kp, tick.dist = 1e5)
kp <- kpPlotBAMDensity(kp, data = un1.bam.file, window.size = window.size, r0=0.5, r1=1, ymax=50000, col="darkorange")
kp <- kpPlotBAMDensity(kp, data = un3.bam.file, window.size = window.size, r0=0.5, r1=0, ymax=50000, col="darkorchid") #using r0>r1 we can flip the plot
kpAxis(kp, ymin=0, ymax=50000, r0=0.5, r1=1, labels = c("0", "25K", "50K"))
kpAxis(kp, ymin=0, ymax=50000, r0=0.5, r1=0, labels = c("0", "25K", "50K"))

kpText(kp, chr = "chr4", x=7e5, y=0.85, labels = paste0("Untreated 1 (reads per ", window.size, " bases)"))
kpText(kp, chr = "chr4", x=7e5, y=0.15, labels = paste0("Untreated 3 (reads per ", window.size, " bases)"))



#Or normalizing by the number of mapped reads
kp <- plotKaryotype(genome="dm6", chromosomes="chr4") #The pasilla data comes from drosophila
kp <- kpAddBaseNumbers(kp, tick.dist = 1e5)
kp <- kpPlotBAMDensity(kp, data = un1.bam.file, window.size = window.size, normalize=TRUE, r0=0.5, r1=1, ymax=0.2, col="darkorange")
kp <- kpPlotBAMDensity(kp, data = un3.bam.file, window.size = window.size, normalize=TRUE, r0=0.5, r1=0, ymax=0.2, col="darkorchid") #using r0>r1 we can flip the plot

Description

Plots the wiggle values in a BigWig file. This function does not work on windows.

Usage

kpPlotBigWig(karyoplot, data, ymin=NULL, ymax="global", data.panel=1, r0=NULL, r1=NULL, col=NULL, border=NULL, clipping=TRUE, ...)

Arguments

Details

kpPlotBigWig plots the data contained in a binary file format called BigWig. BigWig are used to efficiently store numeric values computed for windows covering the whole genome, ususally the coverage from an NGS experiment such as ChIP-seq. Only data required for the plotted region is loaded, and when more than one chromosome is visible, it will load the data for one crhomosome at a time. The function accepts either a BigWigFile oject or a character with the path to a valid big wig file. The character can also be a URL to a remote server. In this case data will be loaded transparently using the import function from rtracklayer. The data is plotted using kpArea and therefore it is possible to plot as a single line, a line with shaded area below or as a shaded area only adjusting the col and border parameters.

Value

Returns the original karyoplot object with the data computed (ymax and ymin values used) stored at karyoplot$latest.plot

Note

Since this functions uses rtracklayer BigWig infrastructure and it does not work on windows, this function won't work on windows either.

See Also

plotKaryotype, kpArea, kpPlotBAMDensity

Examples

if (.Platform$OS.type != "windows") {
  bigwig.file <- system.file("extdata", "BRCA.genes.hg19.bw", package = "karyoploteR")
  brca.genes.file <- system.file("extdata", "BRCA.genes.hg19.txt", package = "karyoploteR")
  brca.genes <- toGRanges(brca.genes.file)
  seqlevelsStyle(brca.genes) <- "UCSC"

  kp <- plotKaryotype(zoom = brca.genes[1])
  kp <- kpPlotBigWig(kp, data=bigwig.file, r0=0, r1=0.2)
  kp <- kpPlotBigWig(kp, data=bigwig.file, r0=0.25, r1=0.45, border="red", lwd=2)
  kp <- kpPlotBigWig(kp, data=bigwig.file, r0=0.5, r1=0.7, ymin=0, ymax=1000, border="gold", col=NA)
  kpAxis(kp, r0=0.5, r1=0.7, ymin=0, ymax=1000)
  kp <- kpPlotBigWig(kp, data=bigwig.file, r0=0.75, r1=0.95, ymin=0, ymax="visible.region", border="orchid", col=NA)
  kpAxis(kp, r0=0.75, r1=0.95, ymin=0, ymax=kp$latest.plot$computed.values$ymax)
}

Description

Given a GRanges object, plot the coverage along the genome.

Usage

kpPlotCoverage(karyoplot, data, show.0.cov=TRUE, data.panel=1, r0=NULL, r1=NULL, col="#0e87eb", border=NULL, ymax=NULL, clipping=TRUE, ...)

Arguments

Details

This is one of the high-level, or specialized, plotting functions of karyoploteR. It takes a GRanges object and plots it's coverage, that is, the number of regions overlapping each genomic position. The input can also be a SimpleRleList resulting from computing the coverage with coverage(data). In contrast with the low-level functions such as kpRect, it is not possible to specify the data using independent numeric vectors and the function only takes in the expected object types.

There's more information at the https://bernatgel.github.io/karyoploter_tutorial/karyoploteR tutorial.

Value

Returns the original karyoplot object with the data computed (max.coverage, ymax) stored in latest.plot.

See Also

plotKaryotype, kpPlotRegions, kpBars, kpPlotBAMCoverage, kpPlotDensity

Examples

set.seed(1000)
 
 #Example 2: Do the same with a single bigger set of possibly overlapping regions
 
 kp <- plotKaryotype("hg19", plot.type=1, chromosomes=c("chr1", "chr2"))
 
 regs <- createRandomRegions(nregions = 1000, length.mean = 10000000, length.sd = 1000000,
                             non.overlapping = FALSE, genome = "hg19", mask=NA)
 kpPlotRegions(kp, regs, r0 = 0, r1 = 0.8, col="#AAAAAA")
 
 kpPlotCoverage(kp, regs, ymax = 20, r0=0.8,  r1=1, col="#CCCCFF")
 kpAxis(kp, ymin = 0, ymax= 20, numticks = 2, r0 = 0.8, r1=1)

Description

Plots the density of features along the genome

Usage

kpPlotDensity(karyoplot, data=NULL, window.size=1e6, ymin=NULL, ymax=NULL, data.panel=1, r0=NULL, r1=NULL, clipping=TRUE, ...)

Arguments