Chapter 2 Circular layout

2.1 Coordinate transformation

To map graphics onto the circle, there exist transformations among several coordinate systems. First, there are data coordinate systems in which ranges for x-axes and y-axes are the ranges of original data. Second, there is a polar coordinate system in which these coordinates are mapped onto a circle. Finally, there is a canvas coordinate system in which graphics are really drawn on the graphic device (Figure 2.1). Each cell has its own data coordinate and they are independent. circlize first transforms coordinates from data coordinate system to polar coordinate system and finally transforms into canvas coordinate system. For users, they only need to imagine that each cell is a normal rectangular plotting region (data coordinate) in which x-lim and y-lim are ranges of data in that cell. circlize knows which cell you are in and does all the transformations automatically.

Transformation between different coordinates

Figure 2.1: Transformation between different coordinates

The final canvas coordinate is in fact an ordinary coordinate in the base R graphic system with x-range in (-1, 1) and y-range in (-1, 1) by default. It should be noted that the circular plot is always drawn inside the circle which has radius of 1 (which means it is always a unit circle), and from outside to inside.

2.2 Rules for making the circular plot

The rule for making the circular plot is rather simple. It follows the sequence of initialize layout -> create track -> add graphics -> create track -> add graphics - ... -> clear. Graphics can be added at any time as long as the tracks are created. Details are shown in Figure 2.2 and as follows:

Order of drawing circular layout.

Figure 2.2: Order of drawing circular layout.

  1. Initialize the layout using circos.initialize(). Since circular layout in fact visualizes data which is in categories, there must be at least a categorical variable. Ranges of x values on each category can be specified as a vector or the range itself. See Section 2.3.

  2. Create plotting regions for the new track and add graphics. The new track is created just inside the previously created one. Only after the creation of the track can you add other graphics on it. There are three ways to add graphics in cells.

    • After the creation of the track, use low-level graphic function like circos.points(), circos.lines(), … to add graphics cell by cell. It always involves a for loop and you need to subset the data by the categorical variable manually.
    • Use circos.trackPoints(), circos.trackLines(), … to add simple graphics through all cells simultaneously.
    • Use argument in circos.track() to add graphics immediately after the creation of a certain cell. needs two arguments x and y which are x values and y values that are in the current cell. This subset operation is applied automatically. This is the most recommended way. Section 2.7 gives detailed explanation of using argument.
  3. Repeat step 2 to add more tracks on the circle unless it reaches the center of the circle.

  4. Call circos.clear() to clean up.

As mentioned above, there are three ways to add graphics on a track.

  1. Create plotting regions for the whole track first and then add graphics by specifying sector.index. In the following pseudo code, x1, y1 are data points in a given cell, which means you need to do data subsetting manually.

    In following code, circos.points() and circos.lines() are used separatedly from circos.track(), thus, the index for the sector needs to be explicitly specified by sector.index argument. There is also a track.index argument for both functions, however, the default value is the “current” track index and as the two functions are used just after circos.track(), the “current” track index is what the two functions expect and it can be ommited when calling the two functions.

circos.initialize(sectors, xlim)
for(sector.index in all.sector.index) {
    circos.points(x1, y1, sector.index)
    circos.lines(x2, y2, sector.index)
  1. Add graphics in a batch mode. In following code, circos.trackPoints() and circos.trackLines() need a categorical variable, a vector of x values and a vector of y values. X and y values will be split by the categorical variable and sent to corresponding cell to add the graphics. Internally, this is done by using circos.points() or circos.lines() in a for loop. This way to add graphics would be convenient if users only want to add a specific type of simple graphics (e.g. only points) to the track, but it is not recommended for making complex graphics.

    circos.trackPoints() and circos.trackLines() need a track.index to specify which track to add the graphics. Similarly, since these two are called just after circos.track(), the graphics are added in the newly created track right away.

circos.initialize(sectors, xlim)
circos.trackPoints(sectors, x, y)
circos.trackLines(sectors, x, y)
  1. Use a panel function to add self-defined graphics as soon as the cell has been created. This is the way recommended and you can find most of the code in this book uses circos.track() creates cells one by one and after the creation of a cell, and is executed on this cell immediately. In this case, the “current” sector and “current” track are marked to this cell that you can directly use low-level functions without specifying sector index and track index.

    If you look at following code, you will find the code inside is as natural as using points() or lines() in the normal R graphic system. This is a way to help you think a cell is an “imaginary rectangular plotting region.”

circos.initialize(sectors, xlim)
circos.track(sectors, all_x, all_y, ylim, = function(x, y) {
        circos.points(x, y)
        circos.lines(x, y)

There are several internal variables keeping tracing of the current sector and track when applying circos.track() and circos.update(). Thus, although functions like circos.points(), circos.lines() need to specify the index of sector and track, they will take the current one by default. As a result, if you draw points, lines, text et al just after the creation of the track or cell, you do not need to set the sector index and the track index explicitly and it will be added in the most recently created or updated cell.

2.3 Sectors and tracks

A circular layout is composed of sectors and tracks. As illustrated in Figure 2.3, the red circle is one track and the blue represents one sector. The intersection of a sector and a track is called a cell which can be thought as an imaginary plotting region for data points. In this section, we introduce how to set data ranges on x and y directions in cells.

Sectors and tracks in circular layout.

Figure 2.3: Sectors and tracks in circular layout.

Sectors are first allocated on the circle by circos.initialize(). There must be a categorical variable (say sectors) that on the circle, each sector corresponds to one category. The width of sectors (measured by degree) are proportional to the data range in sectors on x direction (or the circular direction). The data range can be specified as a numeric vector x which has same length as sectors, then x is split by sectors and data ranges are calculated for each sector internally.

Data ranges can also be specified directly by xlim argument. The valid value for xilm is a two-column matrix with same number of rows as number of sectors that each row in xlim corresponds to one sector. If xlim has row names which already cover sector names, row order of xlim is automatically adjusted. If xlim is a vector of length two, all sectors have the same x range.

circos.initialize(sectors, x = x)
circos.initialize(sectors, xlim = xlim)

If sectors is not specified, the row names of xlim are taken as the value for sectors.

circos.initialize(xlim = xlim)

After the initialization of the layout, you may not see anything drawn or only an empty graphical device is opened. That is because no track has been created yet, however, the layout has already been recorded internally.

In the initialization step, not only the width of each sector is assigned, but also the order of sectors on the circle is determined. Order of the sectors are determined by the order of levels of the input factor. If the value for sectors is not a factor, the order of sectors is unique(sectors). Thus, if you want to change the order of sectors, you can just change of the level of sectors variable. The following code generates plots with different sector orders (Figure 2.4).

sectors = c("d", "f", "e", "c", "g", "b", "a")
s1 = factor(sectors)
circos.initialize(s1, xlim = c(0, 1))
s2 = factor(sectors, levels = sectors)
circos.initialize(s2, xlim = c(0, 1))
Different sector orders.

Figure 2.4: Different sector orders.

In different tracks, cells in the same sector share the same data range on x-axes. Then, for each track, we only need to specify the data range on y direction (or the radical direction) for cells. Similar as circos.initialize(), circos.track() also receives either y or ylim argument to specify the range of y-values. Since all cells in a same track share a same y range, ylim is just a vector of length two if it is specified.

x can also be specified in circos.track(), but it is only used to send to In Section 2.7, we will introduce how x and y are sent to each cell and how the graphics are added.

circos.track(sectors, y = y)
circos.track(sectors, ylim = c(0, 1))
circos.track(sectors, x = x, y = y)

In the track creation step, since all sectors have already been allocated in the circle, if sectors argument is not set, circos.track() would create plotting regions for all available sectors. Also, levels of sectors do not need to be specified explicitly because the order of sectors has already be determined in the initialization step. If users only create cells for a subset of sectors in the track (not all sectors), in fact, cells in remaining unspecified sectors are created as well, but with no borders (pretending they are not created).

# assume `sectors` only covers a subset of sectors
# You will only see cells that are covered in `sectors` have borders
circos.track(sectors, y = y)
# You will see all cells have borders
circos.track(ylim = c(0, 1))
circos.track(ylim = ranges(y))

Cells are basic units in the circular plot and are independent from each other. After the creation of cells, they have self-contained meta values of x-lim and y-lim (data range measured in data coordinate). So if you are adding graphics in one cell, you do not need to consider things outside the cell and also you do not need to consider you are in the circle. Just pretending it is normal rectangle region with its own coordinate.

Sector directions.

Figure 2.5: Sector directions.

Axes directions.

Figure 2.6: Axes directions.

2.4 Graphic parameters

Some basic parameters for the circular layout can be set by circos.par(). These parameters are listed as follows. Note some parameters can only be modified before the initialization of the circular layout.

  • The starting degree where the first sector is put. Note this degree is measured in the standard polar coordinate system which means it is always reverse clockwise. E.g. if it is set to 90, sectors start from the top center of the circle. See Figure 2.5.
  • Gap between two neighbour sectors. It can be a single value which means all gaps share same degree, or a vector which has same number as sectors. Note the first gap is after the first sector. See Figure 2.5 and Figure 2.7.
  • gap.after: Same as, but more understandable. Modifying values of gap.after will also modify and vice versa.
  • track.margin: Like margin in Cascading Style Sheets (CSS), it is the blank area out of the plotting region, also outside of the borders. Since left and right margin are controlled by gap.after, only bottom and top margin need to be set. The value for track.margin is the percentage to the radius of the unit circle. The value can also be set by mm_h()/cm_h()/inches_h() functions with absolute units. See Figure 2.7.
  • cell.padding: Padding of the cell. Like padding in Cascading Style Sheets (CSS), it is the blank area around the plotting regions, but within the borders. The parameter has four values, which control the bottom, left, top and right padding respectively. The first and the third padding values are the percentages to the radius of the unit circle, and the second and fourth values are the degrees. The first and the third value can be set by mm_h()/cm_h()/inches_h() with absolute units. See Figure 2.7.
  • Since curves are simulated by a series of straight lines, this parameter controls the amount of segments to represent a curve. The minimal length of the line segment is the length of the unit circle (\(2\pi\)) divided by More segments means better approximation for the curves, while generate larger file size if figures are in PDF format. See explanantion in Section 3.3.
  • track.height: The default height of tracks. It is the percentage to the radius of the unit circle. The height includes the top and bottom cell paddings but not the margins. The value can be set by mm_h()/cm_h()/inches_h() with absolute units.
  • points.overflow.warning: Since each cell is in fact not a real plotting region but only an ordinary rectangle (or more precisely, a circular rectangle), it does not remove points that are plotted outside of the region. So if some points (or lines, text) are out of the plotting region, by default, the package would continue drawing the points but with warning messages. However, in some circumstances, drawing something out of the plotting region is useful, such as adding some text annotations (like the first track in Figure 1.2). Set this value to FALSE to turn off the warnings.
  • canvas.xlim: The ranges in the canvas coordinate in x direction. circlize is forced to put everything inside the unit circle, so canvas.xlim and canvas.ylim is c(-1, 1) by default. However, you can set it to a more broad interval if you want to leave more spaces out of the circle. By choosing proper canvas.xlim and canvas.ylim, actually you can customize the circle. E.g. setting canvas.xlim to c(0, 1) and canvas.ylim to c(0, 1) would only draw 1/4 of the circle.
  • canvas.ylim: The ranges in the canvas coordinate in y direction.
  • circle.margin: Margin in the horizontal and vertical direction. The value should be a positive numeric vector and the length of it should be either 1, 2, or 4. When it has length of 1, it controls the margin on the four sides of the circle. When it has length of 2, the first value controls the margin on the left and right, and the second value controls the margin on the bottom and top side. When it has length of 4, the four values controls the margins on the left, right, bottom and top sides of the circle. So A value of c(x1, x2, y1, y2) means circos.par(canvas.xlim = c(-(1+x1), 1+x2), canvas.ylim = c(-(1+y1), 1+y2)).
  • clock.wise: The order for drawing sectors. Default is TRUE which means clockwise (Figure 2.5.
  • xaxis.clock.wise: The direction of x-axis in each cell. By default it is clockwise. Note this new parameter was only available from version 0.4.11 (Figure 2.6). Also see more details on this blog post.
Regions in a cell.

Figure 2.7: Regions in a cell.

Default values for graphic parameters are listed in following table. 0 1
track.margin c(0.01, 0.01)
cell.padding c(0.02, 1.00, 0.02, 1.00) 500
track.height 0.2
points.overflow.warning TRUE
canvas.xlim c(-1, 1)
canvas.ylim c(-1, 1)
circle.margin c(0, 0, 0, 0)
clock.wise TRUE
xaxis.clock.wise TRUE

Parameters related to the allocation of sectors cannot be changed after the initialization of the circular layout. Thus,,, canvas.xlim, canvas.ylim, circle.margin, clock.wise and xaxis.clock.wise can only be modified before circos.initialize(). The second and the fourth values of cell.padding (left and right paddings) can not be modified neither (or will be ignored).

Similar reason, since some of the parameters are defined before the initialization of the circular layout, after making each plot, you need to call circos.clear() to manually reset all the parameters.

circos.par() can be used in the same way as options():

circos.par("" = 30)

Or use the $ symbol:

circos.par$ = 30

Use RESET to reset all the options to their default values:

circos.par(RESET = TRUE)

Simply enter circos.par prints the current values of all parameters:

##  Option                  Value           
##  -----------------------:------------------
##            0               
##              1               
##  gap.after               1               
##  track.margin            0.01, 0.01      
##    500             
##  cell.padding            0.02, 1, 0.02, 1
##  track.height            0.2             
##  points.overflow.warning TRUE            
##  circle.margin           0, 0, 0, 0      
##  canvas.xlim             -1, 1           
##  canvas.ylim             -1, 1           
##         10              
##  clock.wise              TRUE            
##  xaxis.clock.wise        TRUE            
##  message                 TRUE            
##  help                    TRUE

circos.par() is aimed to be designed to be independent to the number or the order of sectors, however, there is an exception. The parameter controls the spaces between two neighbouring sectors. When it is set as a scalar, the gap is the same to every two neighbouring sectors and it works fine. It can also be a vector which has the same length as the number of sectors and it can cause problems:

  1. When you change the order of the sectors, you also need to manually change the order of
  2. In chordDiagram() function which will be introduced in Section 14, by default the tiny sectors are removed to improve the visualization, which means, the should be adjusted.
  3. Also in chordDiagram(), sometimes it is not very straightforward to find out the order of sectors, thus, it is difficult to set a proper

Now, from version 0.4.10, the value of can be set as a named vector where the names are the names of the sectors. In this case, the vector can be automatically reordered or subsetted according to the sector ordering in the plot.

2.5 Create plotting regions

As described above, only after creating the plotting region can you add low-level graphics in it. The minimal set of arguments for circos.track() is to set either y or ylim which assigns range of y values for this track. circos.track() creates tracks for all sectors although in some case only parts of them are visible.

If sectors is not specified, all cells in the track will be created with the same settings. If sectors, x and y are set, they need to be vectors with the same length. Proper values of x and y that correspond to current cell will be passed to by subsetting sectors internally. Section 2.7 explains the usage of

Graphic arguments such as bg.border and bg.col can either be a scalar or a vector. If it is a vector, the length must be equal to the number of sectors and the order corresponds to the order of sectors. Thus, you can create plot regions with different styles of borders and background colors.

If you are confused with the sectors orders, you can also customize the borders and background colors inside"cell.xlim")/CELL_META$cell.xlim and"cell.ylim")/CELL_META$cell.ylim give you dimensions of the plotting region and you can customize plot regions directly by e.g.

circos.rect(CELL_META$cell.xlim[1], CELL_META$cell.ylim[1],
            CELL_META$cell.xlim[2], CELL_META$cell.ylim[2], 
            col = "#FF000040", border = 1)

circos.track() provides track.margin and cell.padding arguments that they only control track margins and cell paddings for the current track. Of course the second and fourth value (the left and the right padding) in cell.padding are ignored.

2.6 Update plotting regions

circos.track() creates new tracks, however, if track.index argument is set to a track which already exists, circos.track() actually re-creates this track. In this case, coordinates on y directions can be re-defined, but settings related to the positions of the track such as the height of the track can not be modified.

circos.track(sectors, ylim = c(0, 1), track.index = 1, ...)

For a single cell, circos.update() can be used to erase all graphics that have been already added in the cell. However, the data coordinate in the cell keeps unchanged.

circos.update(sector.index, track.index)
circos.points(x, y, sector.index, track.index)

2.7 argument

The argument in circos.track() is extremely useful to apply plotting as soon as the cell has been created. This self-defined function needs two arguments x and y which are data points that belong to this cell. The value for x and y are automatically extracted from x and y in circos.track() according to the category defined in sectors. In the following example, inside, in sector a, the value of x is 1:3 and in sector b, value of x is 4:5. If x or y in circos.track() is NULL, then x or y inside is also NULL.

sectors = c("a", "a", "a", "b", "b")
x = 1:5
y = 5:1
circos.track(sectors, x = x, y = y, = function(x, y) {
        circos.points(x, y)

Since you can obtain the current sector index in, you can ignore the values from the x and y arguments, while do subsetting by your own:

sectors = c("a", "a", "a", "b", "b")
x2 = 1:5
y2 = 5:1
circos.track(ylim = range(y), = function(x, y) { # here x and y are useless
        l = sectors == CELL_META$sector.index
        circos.points(x2[l], y2[l])

In, one thing important is that if you use any low-level graphic functions, you don’t need to specify sector.index and track.index explicitly. Remember that when applying circos.track(), cells in the track are created one after one. When a cell is created, circlize would set the sector index and track index of the cell as the ‘current’ index. When the cell is created, is executed immediately. Without specifying sector.index and track.index, the ‘current’ ones are used and that’s exactly what you need.

The advantage of is that it makes you feel you are using graphic functions in the base graphic engine (You can see it is almost the same of using circos.points(x, y) and points(x, y)). It will be much easier for users to understand and customize new graphics.

Inside, information of the ‘current’ cell can be obtained through Also this function takes the ‘current’ sector and ‘current’ track by default., sector.index, track.index)

Information that can be extracted by are:

  • sector.index: The name for the sector.
  • sector.numeric.index: Numeric index for the sector.
  • track.index: Numeric index for the track.
  • xlim: Minimal and maximal values on the x-axis.
  • ylim: Minimal and maximal values on the y-axis.
  • xcenter: mean of xlim.
  • ycenter: mean of ylim.
  • xrange: defined as xlim[2] - xlim[1].
  • yrange: defined as ylim[2] - ylim[1].
  • cell.xlim: Minimal and maximal values on the x-axis extended by cell paddings.
  • cell.ylim: Minimal and maximal values on the y-axis extended by cell paddings.
  • xplot: Degree of right and left borders in the plotting region. The values ignore the direction of the circular layout (i.e. whether it is clock wise or not). xplot[1] is always upstream of xplot[2] in the clock-wise direction.
  • yplot: Radius of bottom and top radius in the plotting region.
  • cell.width: Width of the cell, measured in degree. It is calculated as (xplot[1] - xplot[2]) %% 360.
  • cell.height: Height of the cell. Simply yplot[2] - yplot[1].
  • Same as xplot[1].
  • Same as xplot[2].
  • cell.bottom.radius: Same as yplot[1].
  • Same as yplot[2].
  • track.margin: Margins of the cell.
  • cell.padding: Paddings of the cell.

Following example code uses to add sector index in the center of each cell.

circos.track(ylim = ylim, = function(x, y) {
    sector.index ="sector.index")
    xcenter ="xcenter")
    ycenter ="ycenter")
    circos.text(xcenter, ycenter, sector.index)
}) can also be used outside, but you need to explictly specify sector.index and track.index arguments unless the current index is what you want.

There is a companion variable CELL_META which is identical to to get cell meta information, but easier and shorter to write. Actually, the value of CELL_META itself is meaningless, but e.g. CELL_META$sector.index is automatically redirected to"sector.index"). Following code rewrites previous example code with CELL_META.

circos.track(ylim = ylim, = function(x, y) {
    circos.text(CELL_META$xcenter, CELL_META$ycenter, 

Please note CELL_META only extracts information for the “current” cell, thus, it is recommended to use only in

Nevertheless, if you have several lines of code which need to be executed out of, you can flag the specified cell as the “current” cell by set.current.cell(), which can save you from typing too many sector.index = ..., track.index = .... E.g. following code

circos.text("xcenter", sector.index, track.index),
  "ycenter", sector.index, track.index),
  "sector.index", sector.index, track.index),
            sector.index, track.index)

can be simplified to:

set.current.cell(sector.index, track.index)
# or even simpler
circos.text(CELL_META$xcenter, CELL_META$ycenter, CELL_META$sector.index)

2.8 Other utilities

2.8.1 circlize() and reverse.circlize()

circlize transforms data points in several coordinate systems and it is basically done by the core function circlize(). The function transforms from data coordinate (coordinate in the cell) to the polar coordinate and its companion reverse.circlize() transforms from polar coordinate to a specified data coordinate. The default transformation is applied in the current cell.

sectors = c("a", "b")
circos.initialize(sectors, xlim = c(0, 1))
circos.track(ylim = c(0, 1))
# x = 0.5, y = 0.5 in sector a and track 1
circlize(0.5, 0.5, sector.index = "a", track.index = 1)
##      theta  rou
## [1,] 270.5 0.89
# theta = 90, rou = 0.9 in the polar coordinate
reverse.circlize(90, 0.9, sector.index = "a", track.index = 1)
##             x    y
## [1,] 1.519774 0.56
reverse.circlize(90, 0.9, sector.index = "b", track.index = 1)
##              x    y
## [1,] 0.5028249 0.56

You can see the results are different for two reverse.circlize() although it is the same points in the polar coordinate, because they are mapped to different cells.

circlize() and reverse.circlize() can be used to connect two circular plots if they are drawn on a same page. This provides a way to build more complex plots. Basically, the two circular plots share a same polar coordiante, then, the manipulation of circlize->reverse.circlize->circlize can transform coordinate for data points from the first circular plot to the second. In Chapter 13, we use this technique to combine two circular plots where one zooms subset of regions in the other one.

The transformation between polar coordinate and canvas coordinate is simple. circlize has a circlize:::polar2Cartesian() function but this function is not exported.

Following example (Figure 2.8) adds raster image to the circular plot. The raster image is added by rasterImage() which is applied in the canvas coordinate. Note how we change coordinate from data coordinate to canvas coordinate by using circlize() and circlize:::polar2Cartesian().

data = yaml.load_file("")
pokemon_list = data$emojis[1:40]
pokemon_name = sapply(pokemon_list, function(x) x$name)
pokemon_src = sapply(pokemon_list, function(x) x$src)

circos.par("points.overflow.warning" = FALSE)
circos.initialize(pokemon_name, xlim = c(0, 1))
circos.track(ylim = c(0, 1), = function(x, y) {
    pos = circlize:::polar2Cartesian(circlize(CELL_META$xcenter, CELL_META$ycenter))
    image = EBImage::readImage(pokemon_src[CELL_META$sector.numeric.index])
    circos.text(CELL_META$xcenter, CELL_META$cell.ylim[1] - mm_y(2),
        CELL_META$sector.index, facing = "clockwise", niceFacing = TRUE,
        adj = c(1, 0.5), cex = 0.6)
        xleft = pos[1, 1] - 0.05, ybottom = pos[1, 2] - 0.05,
        xright = pos[1, 1] + 0.05, ytop = pos[1, 2]+ 0.05)
}, bg.border = 1, track.height = 0.15)
Add raster image to the circular plot.

Figure 2.8: Add raster image to the circular plot.


In circlize package, there is a circos.raster() function which directly adds raster images. It is introduced in Section 3.11.

2.8.2 Absolute units

For the functions in circlize package, they needs arguments which are lengths measured either in the canvas coordinate or in the data coordinate. E.g. track.height argument in circos.track() corresponds to percent of radius of the unit circle. circlize package is built in the R base graphic system which is not straightforward to define a length with absolute units (e.g. a line of length 2 cm). To solve this problem, circlize provides several functions which convert absolute units to the canvas coordinate or the data coordinate accordingly.

mm_h(), cm_h(), inches_h()/inch_h() functions convert absolute units to the canvas coordinate in the radical direction, which normally define the heights of e.g. tracks. If users want to convert a string height or width to the canvas coordinate, directly use strheight() or strwidth() functions.

mm_h(2) # 2mm
cm_h(1) # 1cm

mm_x(), cm_x(), inches_x()/inch_x(), mm_y(), cm_y(), inches_y()/inch_y() convert absolute units to the data coordinate in the x or y direction. By default, the conversion is applied in the “current” cell, but it can still be used in other cells by specifying sector.index and track.index arguments.

mm_x(1, sector.index, track.index)
mm_y(1, sector.index, track.index)

Since the width of the cell is not identical from the top to the bottom in the cell, for *_x() function, the position on y direction where the convert is applied can be specified by the h argument (measured in data coordinate). By default it is converted at the middle point on y-axis.

mm_x(2, h)

Normally the difference of e.g. mm_x(2) at different y positions in a track is very small (unless the track has very big track.height), so in most cases, you can ignore the setting of h argument.

Following plot (Figure 2.9) is an example of setting absolute units.

sectors = letters[1:10]
circos.par(cell.padding = c(0, 0, 0, 0), track.margin = c(0, 0))
circos.initialize(sectors, xlim = cbind(rep(0, 10), runif(10, 0.5, 1.5)))
circos.track(ylim = c(0, 1), track.height = mm_h(5), = function(x, y) {
        circos.lines(c(0, 0 + mm_x(5)), c(0.5, 0.5), col = "blue")
circos.track(ylim = c(0, 1), track.height = cm_h(1),
    track.margin = c(0, mm_h(2)), = function(x, y) {
        xcenter ="xcenter")
        circos.lines(c(xcenter, xcenter), c(0, cm_y(1)), col = "red")
circos.track(ylim = c(0, 1), track.height = inch_h(1),
    track.margin = c(0, mm_h(5)), = function(x, y) {
        line_length_on_x = cm_x(1*sqrt(2)/2)
        line_length_on_y = cm_y(1*sqrt(2)/2)
        circos.lines(c(0, line_length_on_x), c(0, line_length_on_y), col = "orange")
Setting absolute units

Figure 2.9: Setting absolute units


2.8.3 and circos.clear()

You can get basic information of your current circular plot by The function can be called at any time.

sectors = letters[1:3]
circos.initialize(sectors, xlim = c(1, 2))
## All your sectors:
## [1] "a" "b" "c"
## No track has been created
## Your current sector.index is a
circos.track(ylim = c(0, 1)) = "a", track.index = 1)
## sector index: 'a'
## track index: 1
## xlim: [1, 2]
## ylim: [0, 1]
## cell.xlim: [0.991453, 2.008547]
## cell.ylim: [-0.1, 1.1]
## xplot (degree): [360, 241]
## yplot (radius): [0.79, 0.99]
## cell.width (degree): 119
## cell.height (radius): 0.2
## track.margin: c(0.01, 0.01)
## cell.padding: c(0.02, 1, 0.02, 1)
## Your current sector.index is c
## Your current track.index is 1

It can also add labels to all cells by = TRUE).

You should always call circos.clear() at the end of every circular plot. There are several parameters for circular plot which can only be set before circos.initialize(), thus, before you draw the next circular plot, you need to reset all these parameters.

2.9 Set gaps between tracks

In the older versions, you need to set track.height parameter either in circos.par() or in circos.track() to control the space between tracks. Now there is a new set_track_gap() function which simplifies the setting of gaps between two tracks. With the mm_h()/cm_h()/inch_h() functions, it is very easy to set the gaps with physical units (Figure 2.10).

circos.initialize(letters[1:10], xlim = c(0, 1))
circos.track(ylim = c(0, 1))
set_track_gap(mm_h(2)) # 2mm
circos.track(ylim = c(0, 1))
set_track_gap(cm_h(0.5)) # 0.5cm
circos.track(ylim = c(0, 1))
Setting gaps between tracks.

Figure 2.10: Setting gaps between tracks.