Options

Stack overlapping features vertically using z_stack=True

import genomenotebook as gn
import os

data_path = gn.get_example_data_dir()
gff_path = os.path.join(data_path, "MG1655_U00096.gff3")

g=gn.GenomeBrowser(gff_path,
                   search=False,
                   z_stack=True,
                   bounds=(220000,250000) #specifying bounds avoids loading the whole genome in memory
                   )
g.show()

Selecting feature types and attributes

You can select which feature type to display. The default feature types are ["CDS", "repeat_region", "ncRNA", "rRNA", "tRNA"].

You can inspect the gff file to see what feature types and attributes are available. The parse_gff or parse_genbank functions can conveniently be used for this purpose. You can also use the inspect_feature_types function to output a table of feature types and attributes.

#Choosing the feature types and attributes to display
g=gn.GenomeBrowser(gff_path, 
                   feature_types = ["tRNA","rRNA"],
                   attributes = ["gene","locus_tag","product","gbkey"], #will be displayed when hovering 
                   bounds=(220000,230000), #specifying bounds avoids loading the whole genome in memory
                   init_pos=226000)
g.show()

Changing colors

Modifying features by type

The glyph shown for each feature type is defined through a Glyph object. A custom glyphs dictionnary can be passed to GenomeBrowser to customize the glyphs shown for different features.

glyphs=gn.get_default_glyphs()
glyphs['CDS']

Glyph object with attributes:
    glyph_type: arrow
    colors: ('purple', 'orange')
    height: 1
    alpha: 0.8
    show_name: True
    name_attr: gene

glyphs['repeat_region']

Glyph object with attributes:
    glyph_type: box
    colors: ('grey',)
    height: 0.8
    alpha: 1
    show_name: False
    name_attr: gene

Modifying the default glyphs

glyphs["CDS"].colors= ('blue','green') #two colors can be specified, one for each orientation.

g=gn.GenomeBrowser(gff_path, glyphs=glyphs, init_pos=224000, bounds=(220000,230000), search=False)
g.show()

Defining a new Glyph from scractch

glyphs["rRNA"]=gn.Glyph(glyph_type="box", 
                        colors="red", 
                        height=0.5,
                        show_name=True)         
g=gn.GenomeBrowser(gff_path, 
                   glyphs=glyphs,
                   feature_name={'rRNA':"locus_tag"},
                   init_pos=224000, 
                   bounds=(220000,230000), 
                   search=False)
g.show()

g.glyphs["rRNA"]

Glyph object with attributes:
    glyph_type: box
    colors: ('red',)
    height: 0.5
    alpha: 0.8
    show_name: True
    name_attr: locus_tag

Modifying specific features

You can also access a DataFrame with the characteristics of each feature plotted on the genome browser. These can be modified as you wish to customize your plot.

g.patches.head()

	names	xs	ys	xbox_min	color	alpha	pos	attributes	type	label_y	label_x
0	metQ	(220928, 220928, 220213, 220113, 220213)	(0.05, 0.2, 0.2, 0.125, 0.05)	220213	green	0.8	220520.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.2300	220520.5
1	metI	(221621, 221621, 221068, 220968, 221068)	(0.05, 0.2, 0.2, 0.125, 0.05)	221068	green	0.8	221294.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.2300	221294.5
2	metN	(222645, 222645, 221714, 221614, 221714)	(0.05, 0.2, 0.2, 0.125, 0.05)	221714	green	0.8	222129.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.2300	222129.5
3	gmhB	(222833, 222833, 223308, 223408, 223308)	(0.05, 0.2, 0.2, 0.125, 0.05)	222833	blue	0.8	223120.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.2300	223120.5
4	b0201	(223771, 223771, 225312, 225312)	(0.0875, 0.1625, 0.1625, 0.0875)	223771	red	0.8	224541.5	<span style="color:FireBrick">rRNA</span><br><...	rRNA	0.2675	224541.5

g=gn.GenomeBrowser(gff_path, init_pos=224000, bounds=(220000,230000), search=False)
g.patches.loc[g.patches.names=="metN","color"]="green"
g.show()

Customizing labels

Changing the attribute used as the feature name

You can chose which attribute of the GFF file should be displayed on top of the gene. The feature_name needs to belong to the list of attributes. The default list of attributes is [“locus_tag”,“gene”,“product”].

g=gn.GenomeBrowser(gff_path, 
                   attributes=["protein_id",'gene','product'], 
                   feature_name="protein_id",
                   bounds=(20000,30000),
                   search=False)
g.show()

You can also provide a dictionary to use different names for different feature types

g=gn.GenomeBrowser(gff_path, 
                   attributes=["protein_id",'gene','product','ID'],
                   feature_types=["rRNA","CDS"],
                   feature_name={"CDS":"gene",'rRNA':'ID'},
                   bounds=(220000,230000),
                   search=False)

g.show()

Changing the name of specific features

You can also modify the names of specific features directly in the patches DataFrame

g.patches.head()

	names	xs	ys	xbox_min	color	alpha	pos	attributes	type	label_y	label_x
0	metQ	(220928, 220928, 220213, 220113, 220213)	(0.05, 0.2, 0.2, 0.125, 0.05)	220213	orange	0.8	220520.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.23	220520.5
1	metI	(221621, 221621, 221068, 220968, 221068)	(0.05, 0.2, 0.2, 0.125, 0.05)	221068	orange	0.8	221294.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.23	221294.5
2	metN	(222645, 222645, 221714, 221614, 221714)	(0.05, 0.2, 0.2, 0.125, 0.05)	221714	orange	0.8	222129.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.23	222129.5
3	gmhB	(222833, 222833, 223308, 223408, 223308)	(0.05, 0.2, 0.2, 0.125, 0.05)	222833	purple	0.8	223120.5	<span style="color:FireBrick">CDS</span><br><s...	CDS	0.23	223120.5
4	rna-b0201	(223771, 223771, 225212, 225312, 225212)	(0.05, 0.2, 0.2, 0.125, 0.05)	223771	purple	0.8	224541.5	<span style="color:FireBrick">rRNA</span><br><...	rRNA	0.23	224541.5

g.patches.loc[g.patches.names=="metN","color"]="green"
g.patches.loc[g.patches.names=="metN","names"]="custom"
g.show()

Changing label angle and size

g=gn.GenomeBrowser(gff_path,  
                   label_angle=0,
                   label_font_size="10pt",
                   height=200,
                   feature_height=0.2, #fraction of the annotation track occupied by the features
                   bounds=(20000,30000),
                   attributes=["gene","locus_tag"],
                   search=False,
                   z_stack=True) #z_stack will cause overlapping features to shift so that they are distinct on the y-axis
g.show()

Adding information to be displayed when hovering

Data can be added to the tooltip that appears when hovering. Make sure that the length of the values list equals the number of patches.

g=gn.GenomeBrowser(gff_path=gff_path, bounds=(0,10000), attributes=["gene","product","locus_tag"])
values=np.random.randint(0,10,len(g.patches))
g.add_tooltip_data("data",values)
g.show()

Toolbar location

The location of the toolbar can be changed for each track independently. Placing it above or below can help see all the Bokeh tools available. Valid values are: * “above” * “below” * “left” * “right”

See the Bokeh documentation for more details.

import pandas as pd

data_path = gn.get_example_data_dir()
gff_path = os.path.join(data_path, "MG1655_U00096.gff3")

data=pd.DataFrame(dict(x=np.arange(0,50000,100),
                       y=np.sin(np.arange(0,50000,100))))

g=gn.GenomeBrowser(gff_path=gff_path, 
                bounds=(0,50000),
                toolbar_location="above",
                attributes=["gene","product"],
                search=False)

track = g.add_track(height=200, 
                    toolbar_location="above")

track.bar(data=data, pos="x", y="y")
g.show()