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drawing data one genome, four samples SESSION 2 MARTIN KRZYWINSKI Genome Sciences Center BC Cancer Agency Vancouver, Canada EMBO GLOBAL EXCHANGE LECTURE COURSE: HIGH-THROUGHPUT NEXT GENERATION SEQUENCING APPLIED TO INFECTIOUS DISEASES

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GENOME VISUALIZATION WITH CIRCOS v20140922

Institut Pasteur de Tunis, Tunis, Tunesia Sep 15–25, 2014

EMBO GLOBAL EXCHANGE LECTURE COURSE: HIGH-THROUGHPUT NEXT GENERATION SEQUENCING APPLIED TO INFECTIOUS DISEASES

drawing data—

ne genome, four samples

Genome Sciences Center BC Cancer Agency Vancouver, Canada

SESSION 2

MARTIN KRZYWINSKI

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

drawing and spacing ideograms relative ideogram spacing changing ideogram scale ideogram selection ideogram order drawing ideogram regions chromosome breaks

rdering ideogram regions

cytogenetic bands drawing multiple genomes ideogram progression and orientation relative and absolute ticks

This is the image you will create during this session. It contains chrs 1 & 2 from human and mouse

genomes. Each chromosome occupies 1/4 of the figure.

SESSION FINAL IMAGE

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 1

highlights

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

> cat ../../../data/lm.gene.txt

LmxM.07 425833 429915 LmxM.07.0880 type=gene,strand=+,ID=LmxM. 07.0880,Name=LmxM.07.0880,description=protein+kinase%2C +putative,size=4083,web_id=LmxM.07.0880,locus_tag=LmxM. 07.0880,size=4083,Alias=322488462,401415487,LmxM07.0880,LmxM. 07.0880,LmxM07.0880.1,LmxM07.0880.1:pep LmxM.07 441328 442218 LmxM.07.0900 type=gene,strand=+,ID=LmxM. 07.0900,Name=LmxM.07.0900,description=serine%2Fthreonine+kinase%2C +putative%2Cprotein+kinase%2C+putative,size=891,web_id=LmxM. 07.0900,locus_tag=LmxM. 07.0900,size=891,Alias=322488464,401415491,LmxM07.0900,LmxM. 07.0900,LmxM07.0900.1,LmxM07.0900.1:pep

GENE ANNOTATION INPUT FILE

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/1/etc/circos.conf chromosomes_units = 1000 chromosomes = -/00/ chromosomes_color = /./=white <plots> <plot> type = highlight file = conf(datadir)/lm.gene.txt fill_color = black r1 = dims(ideogram,radius_outer) r0 = dims(ideogram,radius_inner) minsize = 5u stroke_thickness = undef </plot> </plots>

GENES AS HIGHLIGHTS

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/1/etc/circos.conf chromosomes_units = 1000 chromosomes = -/00/ chromosomes_color = /./=white <plots> <plot> type = highlight file = conf(datadir)/lm.gene.txt fill_color = black_a4 r1 = dims(ideogram,radius_outer) r0 = dims(ideogram,radius_inner) minsize = 5u stroke_thickness = undef </plot> </plots>

TRANSPARENCY

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/1/etc/circos.conf chromosomes_units = 1000 chromosomes = -/00/ chromosomes_color = /./=white <plots> <plot> type = highlight file = conf(datadir)/lm.gene.txt fill_color = black_a4 r1 = dims(ideogram,radius_outer) r0 = dims(ideogram,radius_inner) minsize = 5u stroke_thickness = undef <rules> <rule> condition = var(description) =~ /putative/ fill_color = red z = 5 </rule> </rules> </plot> </plots>

RULES TO SHOW PUTATIVE PROTEINS

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 2

heatmaps

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/2/etc/circos.conf <plot> type = heatmap r1 = 0.80r r0 = 0.76r file = conf(datadir)/lm.exp.ah063.txt color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> </plot> <plot> type = heatmap r1 = 0.75r r0 = 0.71r file = conf(datadir)/lm.exp.ah064.txt color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> </plot> ...

HEATMAPS, 4 SAMPLES

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# etc/rules.heatmap.conf <rules> <rule> use = yes condition = var(value) < 1000 show = no </rule> <rule> condition = 1 z = eval(var(value)) </rule> </rules>

HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

The heatmap blocks had many common parameters <plot> type = heatmap r1 = 0.80r r0 = 0.76r file = conf(datadir)/lm.exp.ah063.txt color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> </plot> <plot> type = heatmap r1 = 0.75r r0 = 0.71r file = conf(datadir)/lm.exp.ah064.txt color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> </plot>

IMPORTING COMMON TRACK SETTINGS

# etc/heatmap.conf type = heatmap file = conf(datadir)/lm.exp.ah063.txt color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> # 2/2/etc/circos.conf <plot> <<include heatmap.conf>> r1 = 0.80r r0 = 0.76r </plot> <plot> <<include heatmap.conf>> r1 = 0.75r r0 = 0.71r </plot> ...

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 3

floating histograms

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LmxM.01 14846 16843 LmxM.01.0050 exp_ah063=64,exp_ah064=195,exp_ah065=154,exp_ah066=240, exp_min=64,exp_max=240,exp_avg=163.25,exp_range=176,exp_minah=ah063,exp_maxah=ah066 LmxM.01 27727 28314 LmxM.01.0110 exp_ah063=72,exp_ah064=117,exp_ah065=127,exp_ah066=212, exp_min=72,exp_max=212,exp_avg=132,exp_range=140,exp_minah=ah063,exp_maxah=ah066 The value of each data point is the gene name, e.g. LmxM.01.0050. We can change the value by using a rule <rule> condition = 1 value = eval(var(exp_ah063)) </rule>

IMPORTING COMMON TRACK SETTINGS

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/3/etc/circos.conf <plot> sample = ah063 r1 = 0.78r r0 = 0.74r <<include heatmap.conf>> </plot> ... # etc/heatmap.conf type = heatmap color = reds-8-seq scale_log_base = 0.5 minsize = 25u <<include rules.heatmap.conf>> # etc/rules.heatmap.conf <rules> <rule> condition = 1 value = eval(var(exp_conf(.,sample))) flow = continue </rule> <rule> condition = var(value) < 1000 show = no </rule> <rule> condition = 1 z = eval(var(value)) </rule> </rules>

ABSOLUTE IDEOGRAM SCALE

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/3/etc/circos.conf <plot> type = histogram float = yes r0 = 0.80r r1 = 0.90r fill_color = black stroke_thickness = undef min = 0 max = 300 minsize = 20u <<include etc/axes.conf>> <rules> <rule> condition = 1 value = eval(sqrt(var(exp_max))) valuebase = eval(sqrt(var(exp_min))) #flow = continue </rule> <rule> condition = var(exp_range) < 1000 fill_color = grey z = -10 </rule> <rule> condition = var(exp_range) > 10000 fill_color = red z = 10 </rule> </rules> </plot> </plots>

FLOATING HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/3/etc/circos.conf <backgrounds> use = yes <background> y1 = 50 color = vvlgrey </background> <background> y0 = 150 color = vvlred </background> </backgrounds>

FLOATING HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/3/etc/circos.conf <rules> <rule> condition = 1 value = eval(sqrt(var(exp_max))) valuebase = eval(sqrt(var(exp_min))) flow = continue </rule> <rule> condition = var(exp_range) < 1000 fill_color = grey z = -10 </rule> <rule> condition = var(exp_range) > 10000 fill_color = red z = 10 </rule> </rules>

FLOATING HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 4

scatter plot

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LmxM.01 14846 16843 LmxM.01.0050 exp_ah063=64,exp_ah064=195,exp_ah065=154,exp_ah066=240, exp_min=64,exp_max=240,exp_avg=163.25,exp_range=176,exp_minah=ah063,exp_maxah=ah066 The value of each data point is the gene name, e.g. LmxM.01.0050. We can use the name of the sample at which expression was minimum to draw/hide a point <rule> condition = var(exp_minah) ne “ah063” show = no </rule> As before, we can change the value by using a rule <rule> condition = 1 value = eval(var(exp_ah063)) </rule>

IMPORTING COMMON TRACK SETTINGS

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# etc 2/4/etc.circos.conf glyph_size = 8 <plot> show = yes type = scatter r0 = 0.92r r1 = 0.98r sample = ah063 <<include rules.scatter.conf>> <<include axes.scatter.conf>> </plot> # etc/rules.scatter.conf <rules> <rule> use = no condition = var(exp_range) < 1000 show = no </rule> <rule> condition = 1 value = eval(var(exp_max)) #flow = continue </rule>

SCATTER PLOT

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

<rules> <rule> use = yes condition = var(exp_range) < 1000 show = no </rule> <rule> condition = 1 value = eval(var(exp_max)) flow = continue </rule> <rule> condition = var(exp_maxah) eq "conf(.,sample)" color = red #flow = goto fade if true </rule> <rule> condition = var(exp_minah) eq "conf(.,sample)" color = blue z = -5 #flow = goto fade if true </rule> </rules>

SCATTER PLOT

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

<rules> <rule> condition = var(exp_range) < 1000 show = no </rule> <rule> condition = 1 value = eval(var(exp_max)) flow = continue </rule> <rule> condition = var(exp_maxah) eq "conf(.,sample)" color = red flow = goto fade if true </rule> <rule> condition = var(exp_minah) eq "conf(.,sample)" color = blue z = -5 flow = goto fade if true </rule> <rule> condition = 1 show = no </rule> <rule> tag = fade condition = var(exp_range) < 5000 color = eval(sprintf("%s_a5",var(color))) </rule> <rule> condition = var(exp_range) < 10000 color = eval(sprintf("%s_a3",var(color))) </rule> </rules>

SCATTER PLOT

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

glyph_size = 12 <plot> show = yes type = scatter r0 = 0.92r r1 = 0.92r sample = ah063 <<include rules.scatter.conf>> <<include axes.scatter.conf>> </plot> <plot> show = yes type = scatter r0 = 0.94r r1 = 0.94r sample = ah064 <<include rules.scatter.conf>> <<include axes.scatter.conf>> </plot> <plot> show = yes type = scatter r0 = 0.96r r1 = 0.96r sample = ah065 <<include rules.scatter.conf>> <<include axes.scatter.conf>> </plot> ...

SCATTER PLOT

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 5

resampling data

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

> ls ~/circos/data > cat lm.exp.txt | $CIRCOS/tools/resample/bin/resample -bin 25000 -count > gene.count.txt LmxM.00 0 24999 3 LmxM.00 25000 49999 6 LmxM.00 50000 74999 5 LmxM.00 75000 99999 5 LmxM.00 100000 124999 3 ...

IMPORTING COMMON TRACK SETTINGS

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/5/etc/circos.conf <plot> type = histogram file = conf(datadir)/gene.count.txt r1 = 1r+100p r0 = 1r fill_color = black </plot> # 2/5/etc/ideogram.position.conf radius = 0.8r thickness = 10p fill = yes fill_color = black stroke_thickness = 1 stroke_color = black # 2/5/etc/ticks.conf show_grid = yes <ticks> radius = dims(ideogram,radius_outer) +100p ... <tick> grid = yes grid_start = 1r grid_end = 1r+100p grid_thickness =1p grid_color = grey ... </tick> ...

RESAMPLED HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/5/etc/circos.conf <plots> show = yes ...

SCATTER PLOT

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

LESSON 6

scatter plot with min/max error bars

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/6/etc/circos.conf exp_range_cutoff = 10000 <plot> hide* = no sample = ah066 r1 = 0.99r r0 = 0.80r <<include minmax.conf>> </plot> # minmax.conf hide = conf(quick) type = histogram float = yes color = grey <<include rules.minmax.conf>> # rules.minmax.conf <rules> <<include rules.cutoff.conf>> <rule> condition = 1 value = eval(sqrt(var(exp_max))) valuebase = eval(sqrt(var(exp_min))) flow = continue </rule> </rules> # rules.cutoff.conf <rule> condition = var(exp_range) < conf(exp_range_cutoff) show = no </rule>

FLOATING HISTOGRAM

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/6/etc/circos.conf exp_range_cutoff = 10000 <plot> hide* = no sample = ah066 r1 = 0.99r r0 = 0.80r <<include minmax.scatter.conf>> </plot> # minmax.scatter.conf hide = conf(quick) type = scatter glyph_size = 10 stroke_color = grey stroke_thickness = 1 <<include rules.minmax.scatter.conf>> <<include axes.conf>> # rules.minmax.scatter.conf <<include rules.cutoff.conf>> <rule> condition = 1 value = eval(sqrt(var(exp_conf (.,sample)))) flow = continue </rule> <rule> condition = 1 color = eval(sprintf( "rdbu-4-div-%d",remap_int((var(value)**2-var (exp_min))/var(exp_range),0,1,4,1) )) z = eval(var(value)) </rule> </rules>

SCATTER PLOT ON TOP

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# rules.minmax.scatter.conf <<include rules.cutoff.conf>> <rule> condition = 1 value = eval(sqrt(var(exp_conf(.,sample)))) flow = continue </rule> <rule> condition = 1 # remap_int(X,XMIN,XMAX,TARGETMIN,TARGETMAX) color = eval(sprintf("rdbu-4-div-%d",remap_int((var(value)**2-var(exp_min))/var(exp_range),0,1,4,1))) z = eval(var(value)) </rule> </rules>

COLOR MAPPING BASED ON VALUE

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/6/etc/circos.conf exp_range_cutoff = 2500 # you can set this on the command line > circos -param exp_range_cutoff=2500

USING A DIFFERENT CUTOFF

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples

# 2/6/etc/circos.conf quick = no exp_range_cutoff = 10000

FOUR SAMPLES

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GENOME VISUALIZATION WITH CIRCOS · Session 2 · Drawing data—one genome, four samples