Getting Started

In [1]:

# !pip install pygenomeviz
# !apt install ncbi-blast+ mummer mmseqs2

# !pip install pygenomeviz # !apt install ncbi-blast+ mummer mmseqs2

1. Basic Content¶

1-1. Track¶

In [2]:

from pygenomeviz import GenomeViz

gv = GenomeViz()

track = gv.add_feature_track("tutorial", 1000)
track.add_sublabel()

fig = gv.plotfig()
# gv.savefig("example.png")
# gv.savefig_html("example.html")

from pygenomeviz import GenomeViz gv = GenomeViz() track = gv.add_feature_track("tutorial", 1000) track.add_sublabel() fig = gv.plotfig() # gv.savefig("example.png") # gv.savefig_html("example.html")

1-2. Features¶

In [3]:

from pygenomeviz import GenomeViz

gv = GenomeViz()
gv.set_scale_xticks(ymargin=0.5)

track = gv.add_feature_track("tutorial", 1000)
track.add_sublabel()

# Add features to track
track.add_feature(50, 200, 1)
track.add_feature(250, 460, -1, fc="blue")
track.add_feature(500, 710, 1, fc="lime")
track.add_feature(750, 960, 1, fc="magenta", lw=1.0)

fig = gv.plotfig()

from pygenomeviz import GenomeViz gv = GenomeViz() gv.set_scale_xticks(ymargin=0.5) track = gv.add_feature_track("tutorial", 1000) track.add_sublabel() # Add features to track track.add_feature(50, 200, 1) track.add_feature(250, 460, -1, fc="blue") track.add_feature(500, 710, 1, fc="lime") track.add_feature(750, 960, 1, fc="magenta", lw=1.0) fig = gv.plotfig()

1-3. Styled Features¶

In [4]:

from pygenomeviz import GenomeViz

gv = GenomeViz()
gv.set_scale_bar(ymargin=0.5)

track = gv.add_feature_track("tutorial", (1000, 2000))
track.add_sublabel()

# Add styled features
track.add_feature(1050, 1150, 1, label="arrow")
track.add_feature(1200, 1300, -1, plotstyle="bigarrow", label="bigarrow", fc="red", lw=1)
track.add_feature(1330, 1400, 1, plotstyle="bigbox", label="bigbox", fc="blue", text_kws=dict(rotation=0, hpos="center"))
track.add_feature(1420, 1500, 1, plotstyle="box", label="box", fc="limegreen", text_kws=dict(size=10, color="blue"))
track.add_feature(1550, 1600, 1, plotstyle="bigrbox", label="bigrbox", fc="magenta", ec="blue", lw=1, text_kws=dict(rotation=0, vpos="bottom", hpos="center"))
track.add_feature(1650, 1750, -1, plotstyle="rbox", label="rbox", fc="grey", text_kws=dict(rotation=-45, vpos="bottom"))
track.add_feature(1780, 1880, 1, fc="lime", hatch="o", arrow_shaft_ratio=0.2, label="arrow shaft\n0.2", text_kws=dict(rotation=0, hpos="center"))
track.add_feature(1890, 1990, 1, fc="lime", hatch="/", arrow_shaft_ratio=1.0, label="arrow shaft\n1.0", text_kws=dict(rotation=0, hpos="center"))

fig = gv.plotfig()

from pygenomeviz import GenomeViz gv = GenomeViz() gv.set_scale_bar(ymargin=0.5) track = gv.add_feature_track("tutorial", (1000, 2000)) track.add_sublabel() # Add styled features track.add_feature(1050, 1150, 1, label="arrow") track.add_feature(1200, 1300, -1, plotstyle="bigarrow", label="bigarrow", fc="red", lw=1) track.add_feature(1330, 1400, 1, plotstyle="bigbox", label="bigbox", fc="blue", text_kws=dict(rotation=0, hpos="center")) track.add_feature(1420, 1500, 1, plotstyle="box", label="box", fc="limegreen", text_kws=dict(size=10, color="blue")) track.add_feature(1550, 1600, 1, plotstyle="bigrbox", label="bigrbox", fc="magenta", ec="blue", lw=1, text_kws=dict(rotation=0, vpos="bottom", hpos="center")) track.add_feature(1650, 1750, -1, plotstyle="rbox", label="rbox", fc="grey", text_kws=dict(rotation=-45, vpos="bottom")) track.add_feature(1780, 1880, 1, fc="lime", hatch="o", arrow_shaft_ratio=0.2, label="arrow shaft\n0.2", text_kws=dict(rotation=0, hpos="center")) track.add_feature(1890, 1990, 1, fc="lime", hatch="/", arrow_shaft_ratio=1.0, label="arrow shaft\n1.0", text_kws=dict(rotation=0, hpos="center")) fig = gv.plotfig()

1-4. Segments¶

In [5]:

from pygenomeviz import GenomeViz

gv = GenomeViz()
gv.set_scale_bar(ymargin=0.5)

# Set multi segments on track
genome_size_list = (100000, 180000, 150000)
track = gv.add_feature_track("tutorial", genome_size_list)

for segment in track.segments:
    segment.add_sublabel(f"{segment.name}: {segment.start:,} - {segment.end:,} bp")

fig = gv.plotfig()

from pygenomeviz import GenomeViz gv = GenomeViz() gv.set_scale_bar(ymargin=0.5) # Set multi segments on track genome_size_list = (100000, 180000, 150000) track = gv.add_feature_track("tutorial", genome_size_list) for segment in track.segments: segment.add_sublabel(f"{segment.name}: {segment.start:,} - {segment.end:,} bp") fig = gv.plotfig()

In [6]:

from pygenomeviz import GenomeViz
from pygenomeviz.utils import ColorCycler
ColorCycler.set_cmap("Set3")

features = ((1200, 1500, 1), (1600, 1960, -1), (4200, 4800, 1), (4900, 5180, -1), (5200, 5500, 1), (7000, 7600, -1), (7800, 8200, 1))

gv = GenomeViz()
gv.set_scale_bar(ymargin=0.5)

# Set multi segments on track
target_regions = dict(region1=(1000, 2000), region2=(4000, 5500), region3=(7000, 8200))
track = gv.add_feature_track("tutorial", target_regions)
track.set_segment_sep()

for segment in track.segments:
    segment.add_sublabel(f"{segment.name}: {segment.start:,} - {segment.end:,} bp")
    # Add feature to segment
    for feature in features:
        start, end, strand = feature
        if segment.start <= start <= end <= segment.end:
            segment.add_feature(start, end, strand, fc=ColorCycler(), lw=1.0)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.utils import ColorCycler ColorCycler.set_cmap("Set3") features = ((1200, 1500, 1), (1600, 1960, -1), (4200, 4800, 1), (4900, 5180, -1), (5200, 5500, 1), (7000, 7600, -1), (7800, 8200, 1)) gv = GenomeViz() gv.set_scale_bar(ymargin=0.5) # Set multi segments on track target_regions = dict(region1=(1000, 2000), region2=(4000, 5500), region3=(7000, 8200)) track = gv.add_feature_track("tutorial", target_regions) track.set_segment_sep() for segment in track.segments: segment.add_sublabel(f"{segment.name}: {segment.start:,} - {segment.end:,} bp") # Add feature to segment for feature in features: start, end, strand = feature if segment.start <= start <= end <= segment.end: segment.add_feature(start, end, strand, fc=ColorCycler(), lw=1.0) fig = gv.plotfig()

1-6. Exon Features¶

In [7]:

from pygenomeviz import GenomeViz

exon_regions1 = [(0, 210), (300, 480), (590, 800), (850, 1000), (1030, 1300)]
exon_regions2 = [(1500, 1710), (2000, 2480), (2590, 2800)]
exon_regions3 = [(3000, 3300), (3400, 3690), (3800, 4100), (4200, 4620)]

gv = GenomeViz()
track = gv.add_feature_track("Exon Features", 5000)

# Add exon features
track.add_exon_feature(exon_regions1, strand=1, plotstyle="box", label="box", text_kws=dict(rotation=0, hpos="center"))
track.add_exon_feature(exon_regions2, strand=-1, plotstyle="arrow", label="arrow", text_kws=dict(rotation=0, vpos="bottom", hpos="center"), patch_kws=dict(fc="darkgrey"), intron_patch_kws=dict(ec="red"))
track.add_exon_feature(exon_regions3, strand=1, plotstyle="bigarrow", label="bigarrow", text_kws=dict(rotation=0, hpos="center"), patch_kws=dict(fc="lime", lw=1))

fig = gv.plotfig()

from pygenomeviz import GenomeViz exon_regions1 = [(0, 210), (300, 480), (590, 800), (850, 1000), (1030, 1300)] exon_regions2 = [(1500, 1710), (2000, 2480), (2590, 2800)] exon_regions3 = [(3000, 3300), (3400, 3690), (3800, 4100), (4200, 4620)] gv = GenomeViz() track = gv.add_feature_track("Exon Features", 5000) # Add exon features track.add_exon_feature(exon_regions1, strand=1, plotstyle="box", label="box", text_kws=dict(rotation=0, hpos="center")) track.add_exon_feature(exon_regions2, strand=-1, plotstyle="arrow", label="arrow", text_kws=dict(rotation=0, vpos="bottom", hpos="center"), patch_kws=dict(fc="darkgrey"), intron_patch_kws=dict(ec="red")) track.add_exon_feature(exon_regions3, strand=1, plotstyle="bigarrow", label="bigarrow", text_kws=dict(rotation=0, hpos="center"), patch_kws=dict(fc="lime", lw=1)) fig = gv.plotfig()

1-7. Tracks¶

In [8]:

from pygenomeviz import GenomeViz

genome_list = [
    dict(name="genome 01", size=1000, features=((150, 300, 1), (500, 700, -1), (750, 950, 1))),
    dict(name="genome 02", size=1300, features=((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))),
    dict(name="genome 03", size=1200, features=((150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1))),
]

gv = GenomeViz()
gv.set_scale_xticks()

# Set multi tracks & features
for genome in genome_list:
    name, size, features = genome["name"], genome["size"], genome["features"]
    track = gv.add_feature_track(name, size)
    for feature in features:
        start, end, strand = feature
        track.add_feature(start, end, strand, plotstyle="bigarrow", lw=1.0)

fig = gv.plotfig()

from pygenomeviz import GenomeViz genome_list = [ dict(name="genome 01", size=1000, features=((150, 300, 1), (500, 700, -1), (750, 950, 1))), dict(name="genome 02", size=1300, features=((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))), dict(name="genome 03", size=1200, features=((150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1))), ] gv = GenomeViz() gv.set_scale_xticks() # Set multi tracks & features for genome in genome_list: name, size, features = genome["name"], genome["size"], genome["features"] track = gv.add_feature_track(name, size) for feature in features: start, end, strand = feature track.add_feature(start, end, strand, plotstyle="bigarrow", lw=1.0) fig = gv.plotfig()

1-8. Tracks & Links¶

In [9]:

from pygenomeviz import GenomeViz

genome_list = [
    dict(name="genome 01", size=1000, features=((150, 300, 1), (500, 700, -1), (750, 950, 1))),
    dict(name="genome 02", size=1300, features=((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))),
    dict(name="genome 03", size=1200, features=((150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1))),
]

gv = GenomeViz(track_align_type="center")
gv.set_scale_bar()

# Set multi tracks & features
for genome in genome_list:
    name, size, features = genome["name"], genome["size"], genome["features"]
    track = gv.add_feature_track(name, size)
    track.add_sublabel()
    for idx, feature in enumerate(features, 1):
        start, end, strand = feature
        track.add_feature(start, end, strand, plotstyle="bigarrow", lw=1, label=f"gene{idx:02d}", text_kws=dict(rotation=0, vpos="top", hpos="center"))

# Add links between "genome 01" and "genome 02"
gv.add_link(("genome 01", 150, 300), ("genome 02", 50, 200))
gv.add_link(("genome 01", 700, 500), ("genome 02", 900, 700))
gv.add_link(("genome 01", 750, 950), ("genome 02", 1150, 950))
# Add links between "genome 02" and "genome 03"
gv.add_link(("genome 02", 50, 200), ("genome 03", 150, 300), color="skyblue", inverted_color="lime", curve=True)
gv.add_link(("genome 02", 350, 450), ("genome 03", 450, 350), color="skyblue", inverted_color="lime", curve=True)
gv.add_link(("genome 02", 900, 700), ("genome 03", 700, 500), color="skyblue", inverted_color="lime", curve=True)
gv.add_link(("genome 03", 900, 700), ("genome 02", 1150, 950), color="skyblue", inverted_color="lime", curve=True)

fig = gv.plotfig()

from pygenomeviz import GenomeViz genome_list = [ dict(name="genome 01", size=1000, features=((150, 300, 1), (500, 700, -1), (750, 950, 1))), dict(name="genome 02", size=1300, features=((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))), dict(name="genome 03", size=1200, features=((150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1))), ] gv = GenomeViz(track_align_type="center") gv.set_scale_bar() # Set multi tracks & features for genome in genome_list: name, size, features = genome["name"], genome["size"], genome["features"] track = gv.add_feature_track(name, size) track.add_sublabel() for idx, feature in enumerate(features, 1): start, end, strand = feature track.add_feature(start, end, strand, plotstyle="bigarrow", lw=1, label=f"gene{idx:02d}", text_kws=dict(rotation=0, vpos="top", hpos="center")) # Add links between "genome 01" and "genome 02" gv.add_link(("genome 01", 150, 300), ("genome 02", 50, 200)) gv.add_link(("genome 01", 700, 500), ("genome 02", 900, 700)) gv.add_link(("genome 01", 750, 950), ("genome 02", 1150, 950)) # Add links between "genome 02" and "genome 03" gv.add_link(("genome 02", 50, 200), ("genome 03", 150, 300), color="skyblue", inverted_color="lime", curve=True) gv.add_link(("genome 02", 350, 450), ("genome 03", 450, 350), color="skyblue", inverted_color="lime", curve=True) gv.add_link(("genome 02", 900, 700), ("genome 03", 700, 500), color="skyblue", inverted_color="lime", curve=True) gv.add_link(("genome 03", 900, 700), ("genome 02", 1150, 950), color="skyblue", inverted_color="lime", curve=True) fig = gv.plotfig()

1-9. Chromosomes¶

In [10]:

from pygenomeviz import GenomeViz
from pygenomeviz.utils import ColorCycler
ColorCycler.set_cmap("tab10")

name2chr_segments = dict(
    chimp=dict(chr1=224244399, chr2A=108022953, chr2B=128755405, chr3=196562556, chr4=189151597, chr5=159319378, chr6=168369391, chr7=156046543, chr8=143338810, chr9=110513671, chr10=129809613, chr11=130782606, chr12=130995916, chr13=95599650, chr14=87716528, chr15=80519282, chr16=75912362, chr17=76554115, chr18=74774469, chr19=56733099, chr20=64035432, chr21=33232379, chr22=33698415, chrX=151576176, chrY=26350515),
    human=dict(chr1=248956422, chr2=242193529, chr3=198295559, chr4=190214555, chr5=181538259, chr6=170805979, chr7=159345973, chr8=145138636, chr9=138394717, chr10=133797422, chr11=135086622, chr12=133275309, chr13=114364328, chr14=107043718, chr15=101991189, chr16=90338345, chr17=83257441, chr18=80373285, chr19=58617616, chr20=64444167, chr21=46709983, chr22=50818468, chrX=156040895, chrY=57227415),
    mouse=dict(chr1=195471971, chr2=182113224, chr3=160039680, chr4=156508116, chr5=151834684, chr6=149736546, chr7=145441459, chr8=129401213, chr9=124595110, chr10=130694993, chr11=122082543, chr12=120129022, chr13=120421639, chr14=124902244, chr15=104043685, chr16=98207768, chr17=94987271, chr18=90702639, chr19=61431566, chrX=171031299, chrY=91744698),
)

gv = GenomeViz(fig_track_height=0.7, feature_track_ratio=0.15, track_align_type="center")
gv.set_scale_bar(ymargin=2)

for name, chr_segments in name2chr_segments.items():
    color = ColorCycler()
    # Set chromosomes as segments
    track = gv.add_feature_track(
        name, chr_segments, space=0.01, align_label=False, label_kws=dict(color=color),
    )
    for seg in track.segments:
        seg.add_feature(
            seg.start,
            seg.end,
            plotstyle="bigrbox",
            fc=color,
            ec="black",
            lw=0.5,
            label=seg.name.replace("chr", ""),
            text_kws=dict(rotation=0, size=8, color="white", vpos="center", hpos="center"),
        )

gv.add_link(("human", "chr1", 0, 100000000), ("chimp", "chr1", 0, 100000000))
gv.add_link(("human", "chr2", 0, 120000000), ("chimp", "chr2A", 0, 108022953), color="lime", curve=True)
gv.add_link(("human", "chr2", 120000000, 242193529), ("chimp", "chr2B", 0, 128755405), color="lime", curve=True)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.utils import ColorCycler ColorCycler.set_cmap("tab10") name2chr_segments = dict( chimp=dict(chr1=224244399, chr2A=108022953, chr2B=128755405, chr3=196562556, chr4=189151597, chr5=159319378, chr6=168369391, chr7=156046543, chr8=143338810, chr9=110513671, chr10=129809613, chr11=130782606, chr12=130995916, chr13=95599650, chr14=87716528, chr15=80519282, chr16=75912362, chr17=76554115, chr18=74774469, chr19=56733099, chr20=64035432, chr21=33232379, chr22=33698415, chrX=151576176, chrY=26350515), human=dict(chr1=248956422, chr2=242193529, chr3=198295559, chr4=190214555, chr5=181538259, chr6=170805979, chr7=159345973, chr8=145138636, chr9=138394717, chr10=133797422, chr11=135086622, chr12=133275309, chr13=114364328, chr14=107043718, chr15=101991189, chr16=90338345, chr17=83257441, chr18=80373285, chr19=58617616, chr20=64444167, chr21=46709983, chr22=50818468, chrX=156040895, chrY=57227415), mouse=dict(chr1=195471971, chr2=182113224, chr3=160039680, chr4=156508116, chr5=151834684, chr6=149736546, chr7=145441459, chr8=129401213, chr9=124595110, chr10=130694993, chr11=122082543, chr12=120129022, chr13=120421639, chr14=124902244, chr15=104043685, chr16=98207768, chr17=94987271, chr18=90702639, chr19=61431566, chrX=171031299, chrY=91744698), ) gv = GenomeViz(fig_track_height=0.7, feature_track_ratio=0.15, track_align_type="center") gv.set_scale_bar(ymargin=2) for name, chr_segments in name2chr_segments.items(): color = ColorCycler() # Set chromosomes as segments track = gv.add_feature_track( name, chr_segments, space=0.01, align_label=False, label_kws=dict(color=color), ) for seg in track.segments: seg.add_feature( seg.start, seg.end, plotstyle="bigrbox", fc=color, ec="black", lw=0.5, label=seg.name.replace("chr", ""), text_kws=dict(rotation=0, size=8, color="white", vpos="center", hpos="center"), ) gv.add_link(("human", "chr1", 0, 100000000), ("chimp", "chr1", 0, 100000000)) gv.add_link(("human", "chr2", 0, 120000000), ("chimp", "chr2A", 0, 108022953), color="lime", curve=True) gv.add_link(("human", "chr2", 120000000, 242193529), ("chimp", "chr2B", 0, 128755405), color="lime", curve=True) fig = gv.plotfig()

2. Intermediate Content¶

pyGenomeViz supports genomic feature plots of Genbank and GFF files.

2-1. Genbank¶

2-1-1. Features¶

In [11]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset

gbk_files = load_example_genbank_dataset("yersinia_phage")
gbk = Genbank(gbk_files[0])

gv = GenomeViz(fig_track_height=0.7)
gv.set_scale_bar(ymargin=0.5)

track = gv.add_feature_track(gbk.name, gbk.genome_length)
track.add_sublabel()

# Plot genbank features
features = gbk.extract_features()
track.add_features(features, lw=0.5)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset gbk_files = load_example_genbank_dataset("yersinia_phage") gbk = Genbank(gbk_files[0]) gv = GenomeViz(fig_track_height=0.7) gv.set_scale_bar(ymargin=0.5) track = gv.add_feature_track(gbk.name, gbk.genome_length) track.add_sublabel() # Plot genbank features features = gbk.extract_features() track.add_features(features, lw=0.5) fig = gv.plotfig()

2-1-2. Tracks¶

In [12]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset

gbk_files = load_example_genbank_dataset("yersinia_phage")
gbk_list = list(map(Genbank, gbk_files))

gv = GenomeViz(fig_track_height=0.7)
gv.set_scale_xticks()

for gbk in gbk_list:
    track = gv.add_feature_track(gbk.name, gbk.genome_length)

    # Plot genbank features
    features = gbk.extract_features()
    for feature in features:
        # Set user-defined feature color based on product name
        product = str(feature.qualifiers.get("product", [""])[0])
        color = "lightgrey" if  product.startswith("hypothetical") else "limegreen"
        track.add_features(feature, plotstyle="bigarrow", fc=color, lw=0.5)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset gbk_files = load_example_genbank_dataset("yersinia_phage") gbk_list = list(map(Genbank, gbk_files)) gv = GenomeViz(fig_track_height=0.7) gv.set_scale_xticks() for gbk in gbk_list: track = gv.add_feature_track(gbk.name, gbk.genome_length) # Plot genbank features features = gbk.extract_features() for feature in features: # Set user-defined feature color based on product name product = str(feature.qualifiers.get("product", [""])[0]) color = "lightgrey" if product.startswith("hypothetical") else "limegreen" track.add_features(feature, plotstyle="bigarrow", fc=color, lw=0.5) fig = gv.plotfig()

2-1-3. Contigs per Segment¶

In [13]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset, is_pseudo_feature

gbk_files = load_example_genbank_dataset("mycoplasma_mycoides")
gbk = Genbank(gbk_files[-1])

gv = GenomeViz(fig_track_height=0.5)
gv.set_scale_bar(ymargin=0.5)

# Set contigs as segments
track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), space=0.03)

seqid2features = gbk.get_seqid2features(feature_type=None)
for segment in track.segments:
    # Plot contig features per segment
    features = seqid2features[segment.name]
    for feature in features:
        # Set user-defined feature color based on feature type & pseudo tag
        if feature.type == "CDS":
            color = "grey" if is_pseudo_feature(feature) else "blue"
            segment.add_features(feature, color=color)
        elif feature.type == "rRNA":
            segment.add_features(feature, color="lime")

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset, is_pseudo_feature gbk_files = load_example_genbank_dataset("mycoplasma_mycoides") gbk = Genbank(gbk_files[-1]) gv = GenomeViz(fig_track_height=0.5) gv.set_scale_bar(ymargin=0.5) # Set contigs as segments track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), space=0.03) seqid2features = gbk.get_seqid2features(feature_type=None) for segment in track.segments: # Plot contig features per segment features = seqid2features[segment.name] for feature in features: # Set user-defined feature color based on feature type & pseudo tag if feature.type == "CDS": color = "grey" if is_pseudo_feature(feature) else "blue" segment.add_features(feature, color=color) elif feature.type == "rRNA": segment.add_features(feature, color="lime") fig = gv.plotfig()

2-1-4. Chromosomes¶

In [14]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset, ColorCycler
ColorCycler.set_cmap("tab10")

gbk_files = load_example_genbank_dataset("saccharomyces")
gbk_list = list(map(Genbank, gbk_files))

gv = GenomeViz(fig_track_height=0.7, feature_track_ratio=0.15)
gv.set_scale_bar(ymargin=2.0)

for gbk in gbk_list:
    color = ColorCycler()
    track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), space=0.01, label_kws=dict(color=color))
    track.set_label(track.name.replace("_", "\n"))
    for segment in track.segments:
        segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset, ColorCycler ColorCycler.set_cmap("tab10") gbk_files = load_example_genbank_dataset("saccharomyces") gbk_list = list(map(Genbank, gbk_files)) gv = GenomeViz(fig_track_height=0.7, feature_track_ratio=0.15) gv.set_scale_bar(ymargin=2.0) for gbk in gbk_list: color = ColorCycler() track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), space=0.01, label_kws=dict(color=color)) track.set_label(track.name.replace("_", "\n")) for segment in track.segments: segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5) fig = gv.plotfig()

2-2. GFF¶

2-2-1. Features¶

In [15]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Gff
from pygenomeviz.utils import load_example_gff_file

gff_file = load_example_gff_file("escherichia_coli.gff.gz")
gff = Gff(gff_file)

gv = GenomeViz(fig_track_height=0.5)
gv.set_scale_xticks(start=50000)

track = gv.add_feature_track(name="E.coli", segments=(50000, 80000))
track.add_sublabel()

segment = track.get_segment()
for feature in gff.extract_features("CDS", target_range=segment.range):
    # Get gene name in GFF attributes column (e.g. `gene=araD;`)
    gene_name = str(feature.qualifiers.get("gene", [""])[0])
    # Set user-defined feature color based on gene name
    if gene_name.startswith("ara"):
        color = "blue"
    elif gene_name.startswith("thi"):
        color = "lime"
    elif gene_name in ("pdxA", "surA", "lptD", "djlA", "yabP", "yabQ"):
        color = "tomato"
    else:
        color = "grey"
    segment.add_features(feature, plotstyle="bigarrow", color=color, label_type="gene")

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Gff from pygenomeviz.utils import load_example_gff_file gff_file = load_example_gff_file("escherichia_coli.gff.gz") gff = Gff(gff_file) gv = GenomeViz(fig_track_height=0.5) gv.set_scale_xticks(start=50000) track = gv.add_feature_track(name="E.coli", segments=(50000, 80000)) track.add_sublabel() segment = track.get_segment() for feature in gff.extract_features("CDS", target_range=segment.range): # Get gene name in GFF attributes column (e.g. `gene=araD;`) gene_name = str(feature.qualifiers.get("gene", [""])[0]) # Set user-defined feature color based on gene name if gene_name.startswith("ara"): color = "blue" elif gene_name.startswith("thi"): color = "lime" elif gene_name in ("pdxA", "surA", "lptD", "djlA", "yabP", "yabQ"): color = "tomato" else: color = "grey" segment.add_features(feature, plotstyle="bigarrow", color=color, label_type="gene") fig = gv.plotfig()

2-2-2. Features in Segments¶

In [16]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Gff
from pygenomeviz.utils import load_example_gff_file

gff_file = load_example_gff_file("escherichia_coli.gff.gz")
gff = Gff(gff_file)

gv = GenomeViz()
gv.set_scale_bar(ymargin=0.5)

target_ranges = [(220000, 230000), (300000, 310000)]
track = gv.add_feature_track(name=gff.name, segments=target_ranges)
track.set_segment_sep()

for segment in track.segments:
    segment.add_sublabel()
    # Plot CDS features
    cds_features = gff.extract_features(feature_type="CDS", target_range=segment.range)
    segment.add_features(cds_features, label_type="gene", fc="skyblue", lw=1.0, text_kws=dict(rotation=0, hpos="center"))
    # Plot rRNA features
    rrna_features = gff.extract_features(feature_type="rRNA", target_range=segment.range)
    segment.add_features(rrna_features, label_type="product", hatch="//", fc="lime", lw=1.0)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Gff from pygenomeviz.utils import load_example_gff_file gff_file = load_example_gff_file("escherichia_coli.gff.gz") gff = Gff(gff_file) gv = GenomeViz() gv.set_scale_bar(ymargin=0.5) target_ranges = [(220000, 230000), (300000, 310000)] track = gv.add_feature_track(name=gff.name, segments=target_ranges) track.set_segment_sep() for segment in track.segments: segment.add_sublabel() # Plot CDS features cds_features = gff.extract_features(feature_type="CDS", target_range=segment.range) segment.add_features(cds_features, label_type="gene", fc="skyblue", lw=1.0, text_kws=dict(rotation=0, hpos="center")) # Plot rRNA features rrna_features = gff.extract_features(feature_type="rRNA", target_range=segment.range) segment.add_features(rrna_features, label_type="product", hatch="//", fc="lime", lw=1.0) fig = gv.plotfig()

2-2-3. Contigs per Track¶

In [17]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Gff
from pygenomeviz.utils import load_example_gff_file, is_pseudo_feature

gff_file = load_example_gff_file("mycoplasma_mycoides.gff")
gff = Gff(gff_file)

gv = GenomeViz(fig_track_height=0.5, feature_track_ratio=0.5)
gv.set_scale_xticks(labelsize=10)

# Plot CDS, rRNA features for each contig to tracks
for seqid, size in gff.get_seqid2size().items():
    track = gv.add_feature_track(seqid, size, labelsize=15)
    track.add_sublabel(f"{size:,} bp", size=10, color="grey")
    cds_features = gff.get_seqid2features(feature_type="CDS")[seqid]
    # CDS: blue, CDS(pseudo): grey
    for cds_feature in cds_features:
        color = "grey" if is_pseudo_feature(cds_feature) else "blue"
        track.add_features(cds_feature, color=color)
    # rRNA: lime
    rrna_features = gff.get_seqid2features(feature_type="rRNA")[seqid]
    track.add_features(rrna_features, color="lime")

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Gff from pygenomeviz.utils import load_example_gff_file, is_pseudo_feature gff_file = load_example_gff_file("mycoplasma_mycoides.gff") gff = Gff(gff_file) gv = GenomeViz(fig_track_height=0.5, feature_track_ratio=0.5) gv.set_scale_xticks(labelsize=10) # Plot CDS, rRNA features for each contig to tracks for seqid, size in gff.get_seqid2size().items(): track = gv.add_feature_track(seqid, size, labelsize=15) track.add_sublabel(f"{size:,} bp", size=10, color="grey") cds_features = gff.get_seqid2features(feature_type="CDS")[seqid] # CDS: blue, CDS(pseudo): grey for cds_feature in cds_features: color = "grey" if is_pseudo_feature(cds_feature) else "blue" track.add_features(cds_feature, color=color) # rRNA: lime rrna_features = gff.get_seqid2features(feature_type="rRNA")[seqid] track.add_features(rrna_features, color="lime") fig = gv.plotfig()

3. Advanced Content¶

pyGenomeViz supports aligning genomes between Genbank/Fasta files and plotting the alignment result links. Users can select BLAST, MUMmer, and MMseqs as aligner tools.

3-1. BLAST Comparison¶

3-1-1. Genbank¶

In [18]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset
from pygenomeviz.align import Blast, AlignCoord

gbk_files = load_example_genbank_dataset("yersinia_phage")
gbk_list = list(map(Genbank, gbk_files))

gv = GenomeViz(track_align_type="center")
gv.set_scale_bar()

# Plot CDS features
for gbk in gbk_list:
    track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False)
    for seqid, features in gbk.get_seqid2features("CDS").items():
        segment = track.get_segment(seqid)
        segment.add_features(features, plotstyle="bigarrow", fc="limegreen", lw=0.5)

# Run BLAST alignment & filter by user-defined threshold
align_coords = Blast(gbk_list, seqtype="protein").run()
align_coords = AlignCoord.filter(align_coords, length_thr=100, identity_thr=30)

# Plot BLAST alignment links
if len(align_coords) > 0:
    min_ident = int(min([ac.identity for ac in align_coords if ac.identity]))
    color, inverted_color = "grey", "red"
    for ac in align_coords:
        gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident)
    gv.set_colorbar([color, inverted_color], vmin=min_ident)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset from pygenomeviz.align import Blast, AlignCoord gbk_files = load_example_genbank_dataset("yersinia_phage") gbk_list = list(map(Genbank, gbk_files)) gv = GenomeViz(track_align_type="center") gv.set_scale_bar() # Plot CDS features for gbk in gbk_list: track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False) for seqid, features in gbk.get_seqid2features("CDS").items(): segment = track.get_segment(seqid) segment.add_features(features, plotstyle="bigarrow", fc="limegreen", lw=0.5) # Run BLAST alignment & filter by user-defined threshold align_coords = Blast(gbk_list, seqtype="protein").run() align_coords = AlignCoord.filter(align_coords, length_thr=100, identity_thr=30) # Plot BLAST alignment links if len(align_coords) > 0: min_ident = int(min([ac.identity for ac in align_coords if ac.identity])) color, inverted_color = "grey", "red" for ac in align_coords: gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident) gv.set_colorbar([color, inverted_color], vmin=min_ident) fig = gv.plotfig()

3-1-2. Fasta¶

In [19]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Fasta
from pygenomeviz.utils import load_example_fasta_dataset, ColorCycler
from pygenomeviz.align import Blast, AlignCoord
ColorCycler.set_cmap("tab10")

fasta_files = load_example_fasta_dataset("enterobacteria_phage")
fasta_list = list(map(Fasta, fasta_files))

gv = GenomeViz(feature_track_ratio=0.10, fig_track_height=0.8, theme="dark")
gv.set_scale_xticks(ymargin=3)

# Plot complete/contig genomes
for fasta in fasta_list:
    color = ColorCycler()
    track = gv.add_feature_track(fasta.name, fasta.get_seqid2size(), label_kws=dict(color=color))
    for segment in track.segments:
        segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5)
        segment.add_sublabel(ymargin=0.5)

# Run BLAST alignment & filter by user-defined threshold
align_coords = Blast(fasta_list).run()
align_coords = AlignCoord.filter(align_coords, length_thr=100, identity_thr=30)

# Plot BLAST alignment links
if len(align_coords) > 0:
    min_ident = int(min([ac.identity for ac in align_coords if ac.identity]))
    color, inverted_color = "grey", "red"
    for ac in align_coords:
        gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, size=0.95)
    gv.set_colorbar([color, inverted_color], vmin=min_ident, bar_label="Identity")

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Fasta from pygenomeviz.utils import load_example_fasta_dataset, ColorCycler from pygenomeviz.align import Blast, AlignCoord ColorCycler.set_cmap("tab10") fasta_files = load_example_fasta_dataset("enterobacteria_phage") fasta_list = list(map(Fasta, fasta_files)) gv = GenomeViz(feature_track_ratio=0.10, fig_track_height=0.8, theme="dark") gv.set_scale_xticks(ymargin=3) # Plot complete/contig genomes for fasta in fasta_list: color = ColorCycler() track = gv.add_feature_track(fasta.name, fasta.get_seqid2size(), label_kws=dict(color=color)) for segment in track.segments: segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5) segment.add_sublabel(ymargin=0.5) # Run BLAST alignment & filter by user-defined threshold align_coords = Blast(fasta_list).run() align_coords = AlignCoord.filter(align_coords, length_thr=100, identity_thr=30) # Plot BLAST alignment links if len(align_coords) > 0: min_ident = int(min([ac.identity for ac in align_coords if ac.identity])) color, inverted_color = "grey", "red" for ac in align_coords: gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, size=0.95) gv.set_colorbar([color, inverted_color], vmin=min_ident, bar_label="Identity") fig = gv.plotfig()

3-2. MUMmer Comparison¶

3-2-1. Genbank¶

In [20]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset, is_pseudo_feature
from pygenomeviz.align import MUMmer

gbk_files = load_example_genbank_dataset("mycoplasma_mycoides")
gbk_list = list(map(Genbank, gbk_files))

gv = GenomeViz()
gv.set_scale_bar()

# Plot CDS, rRNA features for each contig to tracks
for gbk in gbk_list:
    track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False)
    for seqid, features in gbk.get_seqid2features(None).items():
        segment = track.get_segment(seqid)
        for feature in features:
            if feature.type == "CDS":
                # CDS: blue, CDS(pseudo): grey
                color = "grey" if is_pseudo_feature(feature) else "blue"
                segment.add_features(feature, fc=color)
            elif feature.type == "rRNA":
                # rRNA: lime
                segment.add_features(feature, fc="lime")

# Run MUMmer alignment
align_coords = MUMmer(gbk_list).run()

# Plot MUMmer alignment links
if len(align_coords) > 0:
    min_ident = int(min([ac.identity for ac in align_coords if ac.identity]))
    color, inverted_color = "grey", "red"
    for ac in align_coords:
        gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident)
    gv.set_colorbar([color, inverted_color], vmin=min_ident)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset, is_pseudo_feature from pygenomeviz.align import MUMmer gbk_files = load_example_genbank_dataset("mycoplasma_mycoides") gbk_list = list(map(Genbank, gbk_files)) gv = GenomeViz() gv.set_scale_bar() # Plot CDS, rRNA features for each contig to tracks for gbk in gbk_list: track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False) for seqid, features in gbk.get_seqid2features(None).items(): segment = track.get_segment(seqid) for feature in features: if feature.type == "CDS": # CDS: blue, CDS(pseudo): grey color = "grey" if is_pseudo_feature(feature) else "blue" segment.add_features(feature, fc=color) elif feature.type == "rRNA": # rRNA: lime segment.add_features(feature, fc="lime") # Run MUMmer alignment align_coords = MUMmer(gbk_list).run() # Plot MUMmer alignment links if len(align_coords) > 0: min_ident = int(min([ac.identity for ac in align_coords if ac.identity])) color, inverted_color = "grey", "red" for ac in align_coords: gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident) gv.set_colorbar([color, inverted_color], vmin=min_ident) fig = gv.plotfig()

3-2-2. Fasta¶

In [21]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Fasta
from pygenomeviz.utils import load_example_fasta_dataset, ColorCycler
from pygenomeviz.align import MUMmer
ColorCycler.set_cmap("Set3")

fasta_files = load_example_fasta_dataset("mycoplasma_mycoides")
fasta_list = list(map(Fasta, fasta_files))

gv = GenomeViz(feature_track_ratio=0.10, track_align_type="center", theme="dark")
gv.set_scale_bar()

# Plot complete/contig genomes
for fasta in fasta_list:
    color = ColorCycler()
    track = gv.add_feature_track(fasta.name, fasta.get_seqid2size(), label_kws=dict(color=color))
    for segment in track.segments:
        segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5)

# Run MUMmer alignment
align_coords = MUMmer(fasta_list).run()

# Plot MUMmer alignment links
if len(align_coords) > 0:
    min_ident = int(min([ac.identity for ac in align_coords if ac.identity]))
    color, inverted_color = "grey", "red"
    for ac in align_coords:
        gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, curve=True)
    gv.set_colorbar([color, inverted_color], vmin=min_ident)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Fasta from pygenomeviz.utils import load_example_fasta_dataset, ColorCycler from pygenomeviz.align import MUMmer ColorCycler.set_cmap("Set3") fasta_files = load_example_fasta_dataset("mycoplasma_mycoides") fasta_list = list(map(Fasta, fasta_files)) gv = GenomeViz(feature_track_ratio=0.10, track_align_type="center", theme="dark") gv.set_scale_bar() # Plot complete/contig genomes for fasta in fasta_list: color = ColorCycler() track = gv.add_feature_track(fasta.name, fasta.get_seqid2size(), label_kws=dict(color=color)) for segment in track.segments: segment.add_feature(segment.start, segment.end, plotstyle="bigrbox", fc=color, lw=0.5) # Run MUMmer alignment align_coords = MUMmer(fasta_list).run() # Plot MUMmer alignment links if len(align_coords) > 0: min_ident = int(min([ac.identity for ac in align_coords if ac.identity])) color, inverted_color = "grey", "red" for ac in align_coords: gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, curve=True) gv.set_colorbar([color, inverted_color], vmin=min_ident) fig = gv.plotfig()

3-3. MMseqs Comparison¶

3-3-1. Genbank¶

In [22]:

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import load_example_genbank_dataset
from pygenomeviz.align import MMseqs

gbk_files = load_example_genbank_dataset("enterobacteria_phage")
gbk_list = list(map(Genbank, gbk_files))

gv = GenomeViz(fig_track_height=0.8, feature_track_ratio=0.4)
gv.set_scale_xticks()

# Plot CDS features
for gbk in gbk_list:
    track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False)
    for seqid, features in gbk.get_seqid2features("CDS").items():
        segment = track.get_segment(seqid)
        segment.add_features(features, fc="skyblue", lw=0.5)

# Run MMseqs RBH search
align_coords = MMseqs(gbk_list).run()

# Plot MMseqs RBH search links
if len(align_coords) > 0:
    min_ident = int(min([ac.identity for ac in align_coords if ac.identity]))
    color, inverted_color = "chocolate", "limegreen"
    for ac in align_coords:
        gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, curve=True)
    gv.set_colorbar([color, inverted_color], vmin=min_ident)

fig = gv.plotfig()

from pygenomeviz import GenomeViz from pygenomeviz.parser import Genbank from pygenomeviz.utils import load_example_genbank_dataset from pygenomeviz.align import MMseqs gbk_files = load_example_genbank_dataset("enterobacteria_phage") gbk_list = list(map(Genbank, gbk_files)) gv = GenomeViz(fig_track_height=0.8, feature_track_ratio=0.4) gv.set_scale_xticks() # Plot CDS features for gbk in gbk_list: track = gv.add_feature_track(gbk.name, gbk.get_seqid2size(), align_label=False) for seqid, features in gbk.get_seqid2features("CDS").items(): segment = track.get_segment(seqid) segment.add_features(features, fc="skyblue", lw=0.5) # Run MMseqs RBH search align_coords = MMseqs(gbk_list).run() # Plot MMseqs RBH search links if len(align_coords) > 0: min_ident = int(min([ac.identity for ac in align_coords if ac.identity])) color, inverted_color = "chocolate", "limegreen" for ac in align_coords: gv.add_link(ac.query_link, ac.ref_link, color=color, inverted_color=inverted_color, v=ac.identity, vmin=min_ident, curve=True) gv.set_colorbar([color, inverted_color], vmin=min_ident) fig = gv.plotfig()