Gallery Example

In [1]:

# %pip install pygenomeviz

# %pip install pygenomeviz

1. Escherichia phage¶

In [2]:

from pygenomeviz import Genbank, GenomeViz, load_example_dataset

gv = GenomeViz(
    fig_width=12,
    feature_track_ratio=0.4,
    align_type="center",
)

gbk_files, links = load_example_dataset("escherichia_phage")
for gbk_file in gbk_files:
    gbk = Genbank(gbk_file)
    track = gv.add_feature_track(gbk.name, gbk.range_size)
    track.add_genbank_features(gbk, size_ratio=0.5, arrow_shaft_ratio=1.0, linewidth=0.5)

for link in links:
    link_data1 = (link.ref_name, link.ref_start, link.ref_end)
    link_data2 = (link.query_name, link.query_start, link.query_end)
    gv.add_link(link_data1, link_data2, curve=True)

fig = gv.plotfig()

from pygenomeviz import Genbank, GenomeViz, load_example_dataset gv = GenomeViz( fig_width=12, feature_track_ratio=0.4, align_type="center", ) gbk_files, links = load_example_dataset("escherichia_phage") for gbk_file in gbk_files: gbk = Genbank(gbk_file) track = gv.add_feature_track(gbk.name, gbk.range_size) track.add_genbank_features(gbk, size_ratio=0.5, arrow_shaft_ratio=1.0, linewidth=0.5) for link in links: link_data1 = (link.ref_name, link.ref_start, link.ref_end) link_data2 = (link.query_name, link.query_start, link.query_end) gv.add_link(link_data1, link_data2, curve=True) fig = gv.plotfig()

2. Erwinia phage¶

In [3]:

from pygenomeviz import Genbank, GenomeViz, load_example_dataset

gv = GenomeViz(
    fig_width=12,
    fig_track_height=0.7,
    feature_track_ratio=0.5,
    tick_track_ratio=0.3,
    tick_style="axis",
    tick_labelsize=10,
)

gbk_files, links = load_example_dataset("erwinia_phage")
gbk_list = [Genbank(gbk_file) for gbk_file in gbk_files]
for gbk in gbk_list:
    track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=15)
    track.add_genbank_features(gbk, plotstyle="arrow")

min_identity = int(min(link.identity for link in links))
for link in links:
    link_data1 = (link.ref_name, link.ref_start, link.ref_end)
    link_data2 = (link.query_name, link.query_start, link.query_end)
    gv.add_link(link_data1, link_data2, v=link.identity, vmin=min_identity)

# Add subtracks to top track for plotting 'GC content' & 'GC skew'
gv.top_track.add_subtrack(ratio=0.7)
gv.top_track.add_subtrack(ratio=0.7)

fig = gv.plotfig()

# Add label annotation to top track
top_track = gv.top_track  # or, gv.get_track("MT939486") or gv.get_tracks()[0]
label, start, end = "Inverted", 310000 + top_track.offset, 358000 + top_track.offset
center = int((start + end) / 2)
top_track.ax.hlines(1.5, start, end, colors="red", linewidth=1, linestyles="dashed", clip_on=False)
top_track.ax.text(center, 2.0, label, fontsize=12, color="red", ha="center", va="bottom")

# Add fillbox to top track
x, y = (start, start, end, end), (1, -1, -1, 1)
top_track.ax.fill(x, y, fc="lime", linewidth=0, alpha=0.1, zorder=-10)

# Plot GC content for top track
pos_list, gc_content_list = gbk_list[0].calc_gc_content()
pos_list += gv.top_track.offset  # Offset is required if align_type is not 'left'
gc_content_ax = gv.top_track.subtracks[0].ax
gc_content_ax.set_ylim(bottom=0, top=max(gc_content_list))
gc_content_ax.fill_between(pos_list, gc_content_list, alpha=0.2, color="blue")
gc_content_ax.text(gv.top_track.offset, max(gc_content_list) / 2, "GC(%) ", ha="right", va="center", color="blue")

# Plot GC skew for top track
pos_list, gc_skew_list = gbk_list[0].calc_gc_skew()
pos_list += gv.top_track.offset  # Offset is required if align_type is not 'left'
gc_skew_abs_max = max(abs(gc_skew_list))
gc_skew_ax = gv.top_track.subtracks[1].ax 
gc_skew_ax.set_ylim(bottom=-gc_skew_abs_max, top=gc_skew_abs_max)
gc_skew_ax.fill_between(pos_list, gc_skew_list, alpha=0.2, color="red")
gc_skew_ax.text(gv.top_track.offset, 0, "GC skew ", ha="right", va="center", color="red")

# Set colorbar for link
gv.set_colorbar(fig, vmin=min_identity)

from pygenomeviz import Genbank, GenomeViz, load_example_dataset gv = GenomeViz( fig_width=12, fig_track_height=0.7, feature_track_ratio=0.5, tick_track_ratio=0.3, tick_style="axis", tick_labelsize=10, ) gbk_files, links = load_example_dataset("erwinia_phage") gbk_list = [Genbank(gbk_file) for gbk_file in gbk_files] for gbk in gbk_list: track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=15) track.add_genbank_features(gbk, plotstyle="arrow") min_identity = int(min(link.identity for link in links)) for link in links: link_data1 = (link.ref_name, link.ref_start, link.ref_end) link_data2 = (link.query_name, link.query_start, link.query_end) gv.add_link(link_data1, link_data2, v=link.identity, vmin=min_identity) # Add subtracks to top track for plotting 'GC content' & 'GC skew' gv.top_track.add_subtrack(ratio=0.7) gv.top_track.add_subtrack(ratio=0.7) fig = gv.plotfig() # Add label annotation to top track top_track = gv.top_track # or, gv.get_track("MT939486") or gv.get_tracks()[0] label, start, end = "Inverted", 310000 + top_track.offset, 358000 + top_track.offset center = int((start + end) / 2) top_track.ax.hlines(1.5, start, end, colors="red", linewidth=1, linestyles="dashed", clip_on=False) top_track.ax.text(center, 2.0, label, fontsize=12, color="red", ha="center", va="bottom") # Add fillbox to top track x, y = (start, start, end, end), (1, -1, -1, 1) top_track.ax.fill(x, y, fc="lime", linewidth=0, alpha=0.1, zorder=-10) # Plot GC content for top track pos_list, gc_content_list = gbk_list[0].calc_gc_content() pos_list += gv.top_track.offset # Offset is required if align_type is not 'left' gc_content_ax = gv.top_track.subtracks[0].ax gc_content_ax.set_ylim(bottom=0, top=max(gc_content_list)) gc_content_ax.fill_between(pos_list, gc_content_list, alpha=0.2, color="blue") gc_content_ax.text(gv.top_track.offset, max(gc_content_list) / 2, "GC(%) ", ha="right", va="center", color="blue") # Plot GC skew for top track pos_list, gc_skew_list = gbk_list[0].calc_gc_skew() pos_list += gv.top_track.offset # Offset is required if align_type is not 'left' gc_skew_abs_max = max(abs(gc_skew_list)) gc_skew_ax = gv.top_track.subtracks[1].ax gc_skew_ax.set_ylim(bottom=-gc_skew_abs_max, top=gc_skew_abs_max) gc_skew_ax.fill_between(pos_list, gc_skew_list, alpha=0.2, color="red") gc_skew_ax.text(gv.top_track.offset, 0, "GC skew ", ha="right", va="center", color="red") # Set colorbar for link gv.set_colorbar(fig, vmin=min_identity)

3. Enterobacteria phage¶

In [4]:

from matplotlib.lines import Line2D
from matplotlib.patches import Patch

from pygenomeviz import Genbank, GenomeViz, load_example_dataset

gv = GenomeViz(
    fig_width=10,
    fig_track_height=0.5,
    feature_track_ratio=0.5,
    tick_track_ratio=0.5,
    align_type="center",
    tick_style="bar",
    tick_labelsize=10,
)

gbk_files, links = load_example_dataset("enterobacteria_phage")
for idx, gbk_file in enumerate(gbk_files):
    gbk = Genbank(gbk_file)
    track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=10)
    track.add_genbank_features(
        gbk,
        label_type="product" if idx == 0 else None,  # Labeling only top track
        label_handle_func=lambda s : "" if s.startswith("hypothetical") else s,  # Ignore 'hypothetical ~~~' label
        labelsize=8,
        labelvpos="top",
        facecolor="skyblue",
        linewidth=0.5,
        labelrotation=45,
    )

normal_color, inverted_color, alpha = "chocolate", "limegreen", 0.5
min_identity = int(min(link.identity for link in links))
for link in links:
    link_data1 = (link.ref_name, link.ref_start, link.ref_end)
    link_data2 = (link.query_name, link.query_start, link.query_end)
    gv.add_link(link_data1, link_data2, normal_color, inverted_color, alpha, v=link.identity, vmin=min_identity, curve=True)

fig = gv.plotfig()

# Add Legends (Maybe there is a better way)
handles = [
    Line2D([], [], marker=">", color="skyblue", label="CDS", ms=10, ls="none"),
    Patch(color=normal_color, label="Normal Link"),
    Patch(color=inverted_color, label="Inverted Link"),
]
fig.legend(handles=handles, bbox_to_anchor=(1, 1))

# Set colorbar for link
gv.set_colorbar(fig, bar_colors=[normal_color, inverted_color], alpha=alpha, vmin=min_identity, bar_height=0.25, bar_label="Identity", bar_labelsize=10)

from matplotlib.lines import Line2D from matplotlib.patches import Patch from pygenomeviz import Genbank, GenomeViz, load_example_dataset gv = GenomeViz( fig_width=10, fig_track_height=0.5, feature_track_ratio=0.5, tick_track_ratio=0.5, align_type="center", tick_style="bar", tick_labelsize=10, ) gbk_files, links = load_example_dataset("enterobacteria_phage") for idx, gbk_file in enumerate(gbk_files): gbk = Genbank(gbk_file) track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=10) track.add_genbank_features( gbk, label_type="product" if idx == 0 else None, # Labeling only top track label_handle_func=lambda s : "" if s.startswith("hypothetical") else s, # Ignore 'hypothetical ~~~' label labelsize=8, labelvpos="top", facecolor="skyblue", linewidth=0.5, labelrotation=45, ) normal_color, inverted_color, alpha = "chocolate", "limegreen", 0.5 min_identity = int(min(link.identity for link in links)) for link in links: link_data1 = (link.ref_name, link.ref_start, link.ref_end) link_data2 = (link.query_name, link.query_start, link.query_end) gv.add_link(link_data1, link_data2, normal_color, inverted_color, alpha, v=link.identity, vmin=min_identity, curve=True) fig = gv.plotfig() # Add Legends (Maybe there is a better way) handles = [ Line2D([], [], marker=">", color="skyblue", label="CDS", ms=10, ls="none"), Patch(color=normal_color, label="Normal Link"), Patch(color=inverted_color, label="Inverted Link"), ] fig.legend(handles=handles, bbox_to_anchor=(1, 1)) # Set colorbar for link gv.set_colorbar(fig, bar_colors=[normal_color, inverted_color], alpha=alpha, vmin=min_identity, bar_height=0.25, bar_label="Identity", bar_labelsize=10)

4. Mycoplasma gallisepticum¶

In [5]:

from pygenomeviz import Genbank, GenomeViz, load_example_dataset

gv = GenomeViz(
    fig_width=10,
    fig_track_height=0.5,
    feature_track_ratio=0.3,
    tick_track_ratio=0.3,
    align_type="center",
    tick_style="bar",
    tick_labelsize=10,
)

gbk_files, links = load_example_dataset("mycoplasma_gallisepticum")
for gbk_file in gbk_files:
    gbk = Genbank(gbk_file)
    track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=12)
    track.add_genbank_features(gbk, plotstyle="rbox")

for link in links:
    link_data1 = (link.ref_name, link.ref_start, link.ref_end)
    link_data2 = (link.query_name, link.query_start, link.query_end)
    gv.add_link(link_data1, link_data2, normal_color="blue", curve=True)

fig = gv.plotfig()

from pygenomeviz import Genbank, GenomeViz, load_example_dataset gv = GenomeViz( fig_width=10, fig_track_height=0.5, feature_track_ratio=0.3, tick_track_ratio=0.3, align_type="center", tick_style="bar", tick_labelsize=10, ) gbk_files, links = load_example_dataset("mycoplasma_gallisepticum") for gbk_file in gbk_files: gbk = Genbank(gbk_file) track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=12) track.add_genbank_features(gbk, plotstyle="rbox") for link in links: link_data1 = (link.ref_name, link.ref_start, link.ref_end) link_data2 = (link.query_name, link.query_start, link.query_end) gv.add_link(link_data1, link_data2, normal_color="blue", curve=True) fig = gv.plotfig()

5. Escherichia coli¶

In [6]:

from pygenomeviz import Genbank, GenomeViz, load_example_dataset

gv = GenomeViz(
    fig_width=10,
    fig_track_height=0.5,
    feature_track_ratio=0.3,
    tick_track_ratio=0.3,
    align_type="center",
    tick_style="bar",
    tick_labelsize=10,
    # Lowerling 'plot_size_thr' will display more features on track
    # This parameter is used for reducing rendering time of large genome dataset
    # In most cases, displaying all features in large genome will result in bad figure
    plot_size_thr=0.0005,
)

gbk_files, links = load_example_dataset("escherichia_coli")
for gbk_file in gbk_files:
    gbk = Genbank(gbk_file)
    track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=12)
    track.add_genbank_features(gbk, plotstyle="box")

for link in links:
    link_data1 = (link.ref_name, link.ref_start, link.ref_end)
    link_data2 = (link.query_name, link.query_start, link.query_end)
    gv.add_link(link_data1, link_data2)

fig = gv.plotfig()

from pygenomeviz import Genbank, GenomeViz, load_example_dataset gv = GenomeViz( fig_width=10, fig_track_height=0.5, feature_track_ratio=0.3, tick_track_ratio=0.3, align_type="center", tick_style="bar", tick_labelsize=10, # Lowerling 'plot_size_thr' will display more features on track # This parameter is used for reducing rendering time of large genome dataset # In most cases, displaying all features in large genome will result in bad figure plot_size_thr=0.0005, ) gbk_files, links = load_example_dataset("escherichia_coli") for gbk_file in gbk_files: gbk = Genbank(gbk_file) track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=12) track.add_genbank_features(gbk, plotstyle="box") for link in links: link_data1 = (link.ref_name, link.ref_start, link.ref_end) link_data2 = (link.query_name, link.query_start, link.query_end) gv.add_link(link_data1, link_data2) fig = gv.plotfig()