- Programming in circlizePlus is summarized into 5 addition rules, which are simple and clear.
- Like ggplot2, it makes programming circular visualizations in the form of addition of plotting functions.
- In ggplot2, the data parameter of the function that draws geometric figures can be missing, and it will use the data parameter value in the ggplot() function. circlizePlus implements similar functionality. In circlizePlus, the function that draws geometric figures can get the default coordinate data (such as x, y) from the track it belongs to.
- Like ggplot2, it supports data mapping. The coordinate parameters are mapped to the default values by passing in an anonymous function of the form "function(x,y){...}".
It is recommended that you have the latest version of the R environment installed. You need to install devtools and load it into the R environment, and then you can install circlizePlus from Github.
if (!requireNamespace("devtools", quietly=TRUE))
install.packages("devtools")
install_github("TianzeLab/circlizePlus")Every time you reboot the R environment, you need to load circlizePlus again.
library(circlizePlus)
We are grateful to Dr. Zuguang Gu from DFKZ for his invaluable guidance and support throughout the project.
Dr. Gu has written a book("Circular Visualization in R") explaining how circlize works. To illustrate the similarities and differences between circlize and cirzelizePlus, we've rewritten the code in the book as sample code. Visit circlizePlusBook for details.
ccPlot(contain n ccPars)+ccPar=ccPlot(contain n+1 ccPars),n≥0
ccPlot(contain n ccTracks)+ccTrack=ccPlot(contain n+1 ccTracks),n≥0
ccPlot(contain n ccLinks)+ccLink=ccPlot(contain n+1 ccLinks),n≥0
ccTrak(contain n ccTrakGeoms)+ccTrackGeom=ccTrack(contain n+1 ccTrackGeoms),n≥0
ccTrack(contain n ccCells)+ccCell=ccTrack(contain n+1 ccCells),n≥0
ccCell(contain n ccCellGeoms)+ccCellGeom=ccCell(contain n+1 ccCellGeoms),n≥0
- ccCell: Generate a cell container that belongs to a particular sector.
- ccCells: A list of multiple
ccCell. AnyccCellGeomandccCellsare added together as if they were added to eachccCellcontained in theccCells.
- Class: ccPlot-class
- Function: ccPlot()
- Class: ccPar-class
- Function: ccPar()
- Class: ccCell-class, ccCells-class
- Function: ccCell(), ccCells()
- Class: ccCellGeom-class, ccGenomicCellGeom-class
- Function: ccText(), ccPoints(), ccLines(), ccSegments(), ccRect(), ccPolygon(), ccXaxis(), ccYaxis(), ccBarplot(), ccBoxplot(), ccViolin(), ccArrow(), ccRaster(), ccDendrogram(), ccGenomicPoints(), ccGenomicLines(), ccGenomicRect(), ccGenomicText(), ccGenomicAxis()
- Class: ccTrack-class, ccGenomicTrack-class
- Function: ccTrack(), ccTrackHist(), ccGenomicTrack(), ccGenomicIdeogram(), ccGenomicHeatmap(), ccGenomicLabels(), ccGenomicRainfall(), ccGenomicDensity()
- Class: ccTrackGeom-class
- Function: ccTrackLines(), ccTrackPoints(), ccTrackText()
- Class: ccLink-class, ccHeatmapLink-class, ccGenomicLink-class
- Function: ccLink(), ccHeatmapLink(), ccGenomicLink()
- Class: ccHeatmap-class
- Function: ccHeatmap()
| ccTrack Constructor | ccGenomicTrack() | ccGenomicTrack() | ccGenomicTrack() | ccGenomicTrack() | ccTrack() | ccTrack() | ccTrack() | ccTrack() | ccTrack() | ccTrack() |
| Parameters in ccTrack Constructor | data | data | data | data | x, y | x, y | x, y | x, y | x, y | x, y |
| ccCellGeom Constructor | ccGenomicPoints() | ccGenomicLines() | ccGenomicRect() | ccGenomicText() | ccLines() | ccPoints() | ccPolygon() | ccText() | ccRect() | ccSegments() |
| Parameters in ccCellGeom Constructor | region, value | region, value | region, value | region, value | x, y | x, y | x, y | x, y | xleft, ybottom, xright, ytop | x0, y0, x1, y1 |
A combination of each column in the table above:
region and value in ccGenomicCellGeom constructor can be NULL or function like function(region,value){...}. The above data can be obtained from the data parameter of ccGenomicTrack.
In the following example code, the region and value in the ccGenomicLines constructor are NULL. Their real data comes from the data value of the corresponding sector in ccGenomicTrack. The region and value in the ccGenomicPoints constructor are function. Their real data is calculated based on the definition of the function.
data = generateRandomBed(nr =30, nc = 2)
all_chr = c("chr1","chr2","chr3","chr4","chr5","chr6","chr7","chr8","chr9","chr10","chr11","chr12","chr13","chr14","chr15","chr16","chr17","chr18","chr19","chr20","chr21","chr22","chrX","chrY")
cc = ccPlot(initMode = "initializeWithIdeogram", plotType=NULL)
t1 = ccGenomicTrack(data=data, numeric.column = 4,
panel.fun=function(region,value,...){
circos.genomicPoints(region,value,...)
})
cells1 = ccCells(sector.indexes = all_chr) + ccGenomicLines(numeric.column=2) + ccGenomicPoints(region=\(region,value){region}, value=\(region,value){value}, numeric.column=2)
t1 = t1 + cells1
show(cc+t1)x, x0, x1, xleft, xright, y, y0, y1, ytop, ybottom in ccCellGeom constructor can be NULL or function like function(x,y){...}. The above data can be obtained from the x and y parameter of ccTrack.
In the following example code, the x and y in the first ccPoints constructor are NULL. Their real data comes from the x and y of the corresponding sector in ccTrack. The y in the second ccPoints constructor are function. Their real data is calculated based on the definition of the function.
sectors = c('a','a','a','a','b','b','b','b','c','c','c','c','d','d','d','d')
x1 = c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4)
y1 = c(1,2,3,4,4,3,2,1,1,1,1,1,1,2,1,2)
cc = ccPlot(initMode = "initialize", sectors = sectors, x = x1)
cells = ccCells(sector.indexes = letters[1:4])
cc_point = ccPoints()
cells = cells + cc_point + ccLines()
track1 = ccTrack(sectors = sectors, x=x1, y = y1,panel.fun = function(x,y){
circos.points(y,x)
})
cell_single = ccCell(sector.index = letters[3]) + ccPoints(y=\(x,y){x-y})
track1 = track1 + cells + cell_single
show(cc + track1)