Use the latest version of Circos and read Circos best practices—these list recent important changes and identify sources of common problems.
If you are having trouble, post your issue to the Circos Google Group and include all files and detailed error logs. Please do not email me directly unless it is urgent—you are much more likely to receive a timely reply from the group.
Don't know what question to ask? Read Points of View: Visualizing Biological Data by Bang Wong, myself and invited authors from the Points of View series.
# 1.4 LINKS AND RULES # # The first data track we will add are links. By using rules, which # are expressions that are evaluated for every link, the formatting # can be dynamically changed based on data values. # # I will also show you how to change the definition of colors, if you # would like to assign different chromosome color scheme to your # figure. karyotype = data/karyotype/karyotype.human.txt chromosomes_units = 1000000 chromosomes_display_default = no chromosomes = /hs[1-4]$/ chromosomes_reverse = /hs/ chromosomes_scale = hs1=0.5r,/hs/=0.5rn chromosomes_radius = hs4:0.9r # In the previous tutorial (1.3), I used chromosomes_colors to change # the color of the ideograms. This approach works well when the only # thing you want to do is change the color of the segments. # # Another way to achieve this is to actually redefine the colors which # are used to color the ideograms. The benefit of doing this is that # whenever you refer to the color (which you can use by using the name # of the chromosome), you get the custom value. # # If you look in the human karyotype file linked to above, you'll see # that each chromosome's color is chrN where N is the number of the # chromosome. Thus, hs1 has color chr1, hs2 has color chr2, and so # on. For convenience, a color can be referenced using 'chr' and 'hs' # prefixes (chr1 and hs1 are the same color). # # Colors are redefined by overwriting color definitions, which are # found in the <colors> block. This block is included below from the # colors_fonts_patterns.conf file, which contains all the default # definitions. To overwrite colors, use a "*" suffix and provide a new # value, which can be a lookup to another color. <colors> chr1* = red chr2* = orange chr3* = green chr4* = blue </colors> # Links are defined in <link> blocks enclosed in a <links> block. The # links start at a radial position defined by 'radius' and have their # control point (adjusts curvature) at the radial position defined by # 'bezier_radius'. In this example, I use the segmental duplication # data set, which connects regions of similar sequence (90%+ # similarity, at least 1kb in size). <links> <link> file = data/5/segdup.txt radius = 0.8r bezier_radius = 0r color = black_a4 thickness = 2 # Rule blocks can be added to any <link> or <plot> block and form a # decision chain that changes how data points (e.g. links, histogram # bins, scatter plot glyphs, etc) are formatted. <rules> # The decision chain is composed of one or more <rule> blocks. <rule> # Each rule has a condition, formatting statements and an optional # 'flow' statement. If the condition is true, the rule is applied to # the data point and no further rules are checked (unless # flow=continue). If the condition is false, the next rule is checked. # # var(X) referrs to the value of variable X for the data point. Here 'intrachr' means intra-chromosomal. condition = var(intrachr) # Any links that are intra-chromosomal will not be shown. Further rules are not tested. show = no </rule> <rule> # This rule is applied to all remaining links, since its condition is always true. condition = 1 # The color of the link is set to the 2nd chromosome in the link # coordinate (link's end). Here eval() is required so that the # expression var(chr2) is evaluated (we want the result of var(chr2), # not the color named "var(chr2)"). Note that for conditions, # evaluation is automatic, but required for all other parameters. color = eval(var(chr2)) # After this rule is applied, the rule chain continues. flow = continue </rule> <rule> # If the link's start is on hs1... condition = from(hs1) # ...set the radial position of the link's start to be close to the ideogram. radius1 = 0.99r </rule> <rule> # Same as the rule above, but applies to the end of the link. condition = to(hs1) # 'radius2' (like chr2, start2, end2) refers to the variable 'radius' of the end of the link. radius2 = 0.99r </rule> </rules> </link> </links> <<include ideogram.conf>> <<include ticks.conf>> <image> <<include etc/image.conf>> </image> <<include etc/colors_fonts_patterns.conf>> <<include etc/housekeeping.conf>>
<ideogram> <spacing> default = 0.005r </spacing> # Ideogram position, fill and outline radius = 0.90r thickness = 20p fill = yes stroke_color = dgrey stroke_thickness = 2p # Minimum definition for ideogram labels. show_label = yes # see etc/fonts.conf for list of font names label_font = default label_radius = dims(image,radius) - 60p label_size = 30 label_parallel = yes </ideogram>
show_ticks = yes show_tick_labels = yes <ticks> radius = 1r color = black thickness = 2p # the tick label is derived by multiplying the tick position # by 'multiplier' and casting it in 'format': # # sprintf(format,position*multiplier) # multiplier = 1e-6 # %d - integer # %f - float # %.1f - float with one decimal # %.2f - float with two decimals # # for other formats, see http://perldoc.perl.org/functions/sprintf.html format = %d <tick> spacing = 5u size = 10p </tick> <tick> spacing = 25u size = 15p show_label = yes label_size = 20p label_offset = 10p format = %d </tick> </ticks>