Phylogenetic Tree

In [1]:

# %pip install pycirclizely

# %pip install pycirclizely

In [2]:

import plotly.io as pio
from IPython.display import HTML

import plotly.io as pio from IPython.display import HTML

1. Simple Tree¶

User can plot the phylogenetic tree with Circos.initialize_from_tree() or track.tree() methods. Both methods return a TreeViz instance, which can be manipulated to set phylogenetic tree annotations such as marker and highlight.

1-1. Default Style¶

In [3]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(tree_file)
fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree(tree_file) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[3]:

1-2. Change Style 1¶

In [4]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    start=20,  # Default: 0
    end=340,  # Default: 360
    r_lim=(10, 100),  # Default: (50, 100)
    line_kws=dict(
        line=dict(color="red", width=2)
    ),  # Default: {}, Change color & linewidth
    align_line_kws=dict(
        line=dict(dash="dashdot", width=1),
    ),  # Default: {}, Change linestyle & linewidth
)
fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree( tree_file, start=20, # Default: 0 end=340, # Default: 360 r_lim=(10, 100), # Default: (50, 100) line_kws=dict( line=dict(color="red", width=2) ), # Default: {}, Change color & linewidth align_line_kws=dict( line=dict(dash="dashdot", width=1), ), # Default: {}, Change linestyle & linewidth ) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[4]:

1-3. Change Style 2¶

In [5]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

# Define 4 types kwargs for `Circos.initialize_from_tree()` method
kwargs_list = [
    dict(outer=True, align_leaf_label=True, ignore_branch_length=False),
    dict(outer=True, align_leaf_label=False, ignore_branch_length=False),
    dict(outer=False, align_leaf_label=True, ignore_branch_length=False),
    dict(outer=True, align_leaf_label=True, ignore_branch_length=True),
]

# Plot trees with different kwargs
tree_file = load_example_tree_file("alphabet.nwk")
html_outputs = []
for kwargs in kwargs_list:
    circos, tv = Circos.initialize_from_tree(
        tree_file,
        r_lim=(60, 100),
        outer=kwargs["outer"],
        align_leaf_label=kwargs["align_leaf_label"],
        ignore_branch_length=kwargs["ignore_branch_length"],
    )
    kwargs_text = "<br>".join([f"{k}: {v}" for k, v in kwargs.items()])
    circos.text(text=kwargs_text, font=dict(size=14))
    fig = circos.plotfig()
    html_outputs.append(HTML(pio.to_html(fig, include_plotlyjs="cdn")))

# Display all figures
for html in html_outputs:
    display(html)  # type: ignore[name-defined]

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file # Define 4 types kwargs for `Circos.initialize_from_tree()` method kwargs_list = [ dict(outer=True, align_leaf_label=True, ignore_branch_length=False), dict(outer=True, align_leaf_label=False, ignore_branch_length=False), dict(outer=False, align_leaf_label=True, ignore_branch_length=False), dict(outer=True, align_leaf_label=True, ignore_branch_length=True), ] # Plot trees with different kwargs tree_file = load_example_tree_file("alphabet.nwk") html_outputs = [] for kwargs in kwargs_list: circos, tv = Circos.initialize_from_tree( tree_file, r_lim=(60, 100), outer=kwargs["outer"], align_leaf_label=kwargs["align_leaf_label"], ignore_branch_length=kwargs["ignore_branch_length"], ) kwargs_text = "
".join([f"{k}: {v}" for k, v in kwargs.items()]) circos.text(text=kwargs_text, font=dict(size=14)) fig = circos.plotfig() html_outputs.append(HTML(pio.to_html(fig, include_plotlyjs="cdn"))) # Display all figures for html in html_outputs: display(html) # type: ignore[name-defined]

1-4. Change Style 3¶

In [6]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

# Define 4 types kwargs for `Circos.initialize_from_tree()` method
kwargs_list = [
    dict(reverse=False, ladderize=False),
    dict(reverse=True, ladderize=False),
    dict(reverse=False, ladderize=True),
    dict(reverse=True, ladderize=True),
]

# Plot trees with different kwargs
tree_file = load_example_tree_file("alphabet.nwk")
html_outputs = []
for kwargs in kwargs_list:
    circos, tv = Circos.initialize_from_tree(
        tree_file,
        line_kws=dict(line=dict(width=1)),
        reverse=kwargs["reverse"],
        ladderize=kwargs["ladderize"],
    )
    kwargs_text = "<br>".join([f"{k}: {v}" for k, v in kwargs.items()])
    circos.text(text=kwargs_text, font=dict(size=14))
    fig = circos.plotfig()
    html_outputs.append(HTML(pio.to_html(fig, include_plotlyjs="cdn")))

# Display all figures
for html in html_outputs:
    display(html)  # type: ignore[name-defined]

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file # Define 4 types kwargs for `Circos.initialize_from_tree()` method kwargs_list = [ dict(reverse=False, ladderize=False), dict(reverse=True, ladderize=False), dict(reverse=False, ladderize=True), dict(reverse=True, ladderize=True), ] # Plot trees with different kwargs tree_file = load_example_tree_file("alphabet.nwk") html_outputs = [] for kwargs in kwargs_list: circos, tv = Circos.initialize_from_tree( tree_file, line_kws=dict(line=dict(width=1)), reverse=kwargs["reverse"], ladderize=kwargs["ladderize"], ) kwargs_text = "
".join([f"{k}: {v}" for k, v in kwargs.items()]) circos.text(text=kwargs_text, font=dict(size=14)) fig = circos.plotfig() html_outputs.append(HTML(pio.to_html(fig, include_plotlyjs="cdn"))) # Display all figures for html in html_outputs: display(html) # type: ignore[name-defined]

1-5. Set Label Properties¶

In [7]:

from pycirclizely import Circos
from pycirclizely.utils import ColorCycler, load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(tree_file)

# Change label color
tv.set_node_label_props("A", font=dict(color="red", size=8))
# Change label color & size
tv.set_node_label_props("D", font=dict(color="blue", size=25))
# Hide label
tv.set_node_label_props("G", font=dict(size=0))
# Change label colors
color_cycler = ColorCycler("T10")
for name in list("MNOPQRSTUVWXY"):
    tv.set_node_label_props(name, font=dict(color=color_cycler.get_color()))

# Add node info in hovertext
tv.show_node_info()

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import ColorCycler, load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree(tree_file) # Change label color tv.set_node_label_props("A", font=dict(color="red", size=8)) # Change label color & size tv.set_node_label_props("D", font=dict(color="blue", size=25)) # Hide label tv.set_node_label_props("G", font=dict(size=0)) # Change label colors color_cycler = ColorCycler("T10") for name in list("MNOPQRSTUVWXY"): tv.set_node_label_props(name, font=dict(color=color_cycler.get_color())) # Add node info in hovertext tv.show_node_info() fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[7]:

1-6. Set Line Properties¶

In [8]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(tree_file, line_kws=dict(line=dict(width=1.0)))

# Change line color on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor)
# node and its descendent nodes
tv.set_node_line_props(["A", "B", "C", "D", "E", "F"], line=dict(color="red"))
# Change line color & width on [G,I] MRCA node and its descendent nodes
tv.set_node_line_props(["G", "I"], line=dict(color="blue", width=2.0))
# Change line color & label color on [M,W] MRCA node and its descendent nodes
tv.set_node_line_props(["M", "W"], apply_label_color=True, line=dict(color="green"))
# Change line color & label color on [R,T] MRCA node and its descendent nodes
tv.set_node_line_props(["R", "T"], apply_label_color=True, line=dict(color="purple"))
# Change line color & style [X,Y] MRCA node
tv.set_node_line_props(
    ["X", "Y"], descendent=False, line=dict(color="purple", dash="dot")
)

# Add node info in hovertext
tv.show_node_info()

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree(tree_file, line_kws=dict(line=dict(width=1.0))) # Change line color on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor) # node and its descendent nodes tv.set_node_line_props(["A", "B", "C", "D", "E", "F"], line=dict(color="red")) # Change line color & width on [G,I] MRCA node and its descendent nodes tv.set_node_line_props(["G", "I"], line=dict(color="blue", width=2.0)) # Change line color & label color on [M,W] MRCA node and its descendent nodes tv.set_node_line_props(["M", "W"], apply_label_color=True, line=dict(color="green")) # Change line color & label color on [R,T] MRCA node and its descendent nodes tv.set_node_line_props(["R", "T"], apply_label_color=True, line=dict(color="purple")) # Change line color & style [X,Y] MRCA node tv.set_node_line_props( ["X", "Y"], descendent=False, line=dict(color="purple", dash="dot") ) # Add node info in hovertext tv.show_node_info() fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[8]:

1-7. Plot Marker¶

In [9]:

from pycirclizely import Circos
from pycirclizely.utils import ColorCycler, load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(tree_file)

# Plot markers on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor)
# node and its descendent nodes
tv.marker(["A", "B", "C", "D", "E", "F"], marker=dict(color="salmon", size=6))
# Plot square marker on [G,K] MRCA node
tv.marker(
    ["G", "K"],
    descendent=False,
    marker=dict(color="orange", symbol="square-dot", size=8),
)
# Plot star markers on [X,Y] MRCA node and its descendent nodes
tv.marker(["X", "Y"], marker=dict(color="lime", symbol="star", size=10))
# Plot colored markers on M,N,O,P,Q,R,S,T,U,V,W leaf nodes
color_cycler = ColorCycler("Set3")
for leaf_name in list("MNOPQRSTUVW"):
    tv.marker(leaf_name, marker=dict(color=color_cycler.get_color(), size=10))

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import ColorCycler, load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree(tree_file) # Plot markers on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor) # node and its descendent nodes tv.marker(["A", "B", "C", "D", "E", "F"], marker=dict(color="salmon", size=6)) # Plot square marker on [G,K] MRCA node tv.marker( ["G", "K"], descendent=False, marker=dict(color="orange", symbol="square-dot", size=8), ) # Plot star markers on [X,Y] MRCA node and its descendent nodes tv.marker(["X", "Y"], marker=dict(color="lime", symbol="star", size=10)) # Plot colored markers on M,N,O,P,Q,R,S,T,U,V,W leaf nodes color_cycler = ColorCycler("Set3") for leaf_name in list("MNOPQRSTUVW"): tv.marker(leaf_name, marker=dict(color=color_cycler.get_color(), size=10)) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[9]:

1-8. Plot Highlight¶

In [10]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(tree_file, line_kws=dict(line=dict(width=1)))

# Plot highlight on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor) node
tv.highlight(["A", "B", "C", "D", "E", "F"], fillcolor="salmon")
# Plot highlight on [G,K] MRCA node
tv.highlight(["G", "K"], fillcolor="orange")
# Plot highlight on L node with black thin dashdot edge line
tv.highlight("L", fillcolor="lime", line=dict(color="black", width=0.5, dash="dashdot"))
# Plot highlight on [N,W] MRCA node with low opacity and red edge line
tv.highlight(
    ["N", "W"], fillcolor="lightgrey", opacity=0.3, line=dict(color="red", width=0.5)
)

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree(tree_file, line_kws=dict(line=dict(width=1))) # Plot highlight on [A,B,C,D,E,F] MRCA(Most Recent Common Ancestor) node tv.highlight(["A", "B", "C", "D", "E", "F"], fillcolor="salmon") # Plot highlight on [G,K] MRCA node tv.highlight(["G", "K"], fillcolor="orange") # Plot highlight on L node with black thin dashdot edge line tv.highlight("L", fillcolor="lime", line=dict(color="black", width=0.5, dash="dashdot")) # Plot highlight on [N,W] MRCA node with low opacity and red edge line tv.highlight( ["N", "W"], fillcolor="lightgrey", opacity=0.3, line=dict(color="red", width=0.5) ) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[10]:

1-9. With Heatmap¶

In [11]:

import numpy as np

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

np.random.seed(0)

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    r_lim=(30, 80),
    # Set large margin to insert heatmap track between tree and labels
    leaf_label_rmargin=24,
    line_kws=dict(line=dict(width=1)),
)

# Plot heatmap
sector = tv.track.parent_sector
track = sector.add_track((80, 100))
track.axis(line=dict(color="grey"))
vmin, vmax, cmap = 0, 100, "RdBu_r"
data = np.random.randint(vmin, vmax + 1, (3, tv.leaf_num))

leaf_labels = tv.leaf_labels
custom_hover_text = [
    f"""Leaf: {leaf_labels[col_idx]}
    <br>Level: {row_idx + 1}
    <br>Value: {data[row_idx, col_idx]}"""
    for row_idx in range(data.shape[0])
    for col_idx in range(data.shape[1])
]
coloraxis = circos.colorbar(vmin=vmin, vmax=vmax, cmap=cmap, orientation="h")
track.heatmap(
    data, cmap=cmap, show_value=True, hover_text=custom_hover_text, coloraxis=coloraxis
)

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import numpy as np from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file np.random.seed(0) tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree( tree_file, r_lim=(30, 80), # Set large margin to insert heatmap track between tree and labels leaf_label_rmargin=24, line_kws=dict(line=dict(width=1)), ) # Plot heatmap sector = tv.track.parent_sector track = sector.add_track((80, 100)) track.axis(line=dict(color="grey")) vmin, vmax, cmap = 0, 100, "RdBu_r" data = np.random.randint(vmin, vmax + 1, (3, tv.leaf_num)) leaf_labels = tv.leaf_labels custom_hover_text = [ f"""Leaf: {leaf_labels[col_idx]}
Level: {row_idx + 1}
Value: {data[row_idx, col_idx]}""" for row_idx in range(data.shape[0]) for col_idx in range(data.shape[1]) ] coloraxis = circos.colorbar(vmin=vmin, vmax=vmax, cmap=cmap, orientation="h") track.heatmap( data, cmap=cmap, show_value=True, hover_text=custom_hover_text, coloraxis=coloraxis ) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[11]:

1-10. With Heatmap + Bar¶

In [12]:

import numpy as np
import pandas as pd

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

np.random.seed(0)

tree_file = load_example_tree_file("alphabet.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    start=5,
    end=355,
    r_lim=(30, 70),
    # Set large margin to insert heatmap & bar track between tree and labels
    leaf_label_rmargin=34,
    ignore_branch_length=True,
    line_kws=dict(line=dict(width=1)),
)
leaf_labels = tv.leaf_labels

# Create example dataframe for heatmap & bar plot
df = pd.DataFrame(
    dict(
        s1=np.random.randint(0, 100, tv.leaf_num),
        s2=np.random.randint(0, 100, tv.leaf_num),
        s3=np.random.randint(0, 100, tv.leaf_num),
        count=np.random.randint(1, 10, tv.leaf_num),
    ),
    index=leaf_labels,
)
print(df.head())

# Plot bar (from `count` column data)
sector = tv.track.parent_sector
bar_track = sector.add_track((85, 100), r_pad_ratio=0.1)
bar_track.axis()
bar_track.grid()
x = np.arange(0, tv.leaf_num) + 0.5
y = df["count"].to_numpy()
custom_hover_text = [
    f"Leaf: {leaf_labels[i]}<br>Count: {val}" for i, val in enumerate(y)
]
bar_track.bar(x, y, width=0.3, hover_text=custom_hover_text, fillcolor="orange")

# Plot heatmaps (from `s1, s2, s3` column data)
track1 = sector.add_track((80, 85))
custom_hover_text = [
    f"Leaf: {leaf_labels[i]}<br>s1: {val}" for i, val in enumerate(df["s1"].to_numpy())
]
track1.heatmap(
    df["s1"].to_numpy(),
    cmap="Reds",
    show_value=True,
    hover_text=custom_hover_text,
    rect_kws=dict(line=dict(color="grey", width=0.5)),
)
track2 = sector.add_track((75, 80))
custom_hover_text = [
    f"Leaf: {leaf_labels[i]}<br>s2: {val}" for i, val in enumerate(df["s2"].to_numpy())
]
track2.heatmap(
    df["s2"].to_numpy(),
    cmap="Blues",
    show_value=True,
    hover_text=custom_hover_text,
    rect_kws=dict(line=dict(color="grey", width=0.5)),
)
track3 = sector.add_track((70, 75))
custom_hover_text = [
    f"Leaf: {leaf_labels[i]}<br>s3: {val}" for i, val in enumerate(df["s3"].to_numpy())
]
track3.heatmap(
    df["s3"].to_numpy(),
    cmap="Greens",
    show_value=True,
    hover_text=custom_hover_text,
    rect_kws=dict(line=dict(color="grey", width=0.5)),
)

# Plot track labels
circos.text("count", r=bar_track.r_center, font=dict(color="orange"))
circos.text("s1", r=track1.r_center, font=dict(color="red"))
circos.text("s2", r=track2.r_center, font=dict(color="blue"))
circos.text("s3", r=track3.r_center, font=dict(color="green"))

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import numpy as np import pandas as pd from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file np.random.seed(0) tree_file = load_example_tree_file("alphabet.nwk") circos, tv = Circos.initialize_from_tree( tree_file, start=5, end=355, r_lim=(30, 70), # Set large margin to insert heatmap & bar track between tree and labels leaf_label_rmargin=34, ignore_branch_length=True, line_kws=dict(line=dict(width=1)), ) leaf_labels = tv.leaf_labels # Create example dataframe for heatmap & bar plot df = pd.DataFrame( dict( s1=np.random.randint(0, 100, tv.leaf_num), s2=np.random.randint(0, 100, tv.leaf_num), s3=np.random.randint(0, 100, tv.leaf_num), count=np.random.randint(1, 10, tv.leaf_num), ), index=leaf_labels, ) print(df.head()) # Plot bar (from `count` column data) sector = tv.track.parent_sector bar_track = sector.add_track((85, 100), r_pad_ratio=0.1) bar_track.axis() bar_track.grid() x = np.arange(0, tv.leaf_num) + 0.5 y = df["count"].to_numpy() custom_hover_text = [ f"Leaf: {leaf_labels[i]}
Count: {val}" for i, val in enumerate(y) ] bar_track.bar(x, y, width=0.3, hover_text=custom_hover_text, fillcolor="orange") # Plot heatmaps (from `s1, s2, s3` column data) track1 = sector.add_track((80, 85)) custom_hover_text = [ f"Leaf: {leaf_labels[i]}
s1: {val}" for i, val in enumerate(df["s1"].to_numpy()) ] track1.heatmap( df["s1"].to_numpy(), cmap="Reds", show_value=True, hover_text=custom_hover_text, rect_kws=dict(line=dict(color="grey", width=0.5)), ) track2 = sector.add_track((75, 80)) custom_hover_text = [ f"Leaf: {leaf_labels[i]}
s2: {val}" for i, val in enumerate(df["s2"].to_numpy()) ] track2.heatmap( df["s2"].to_numpy(), cmap="Blues", show_value=True, hover_text=custom_hover_text, rect_kws=dict(line=dict(color="grey", width=0.5)), ) track3 = sector.add_track((70, 75)) custom_hover_text = [ f"Leaf: {leaf_labels[i]}
s3: {val}" for i, val in enumerate(df["s3"].to_numpy()) ] track3.heatmap( df["s3"].to_numpy(), cmap="Greens", show_value=True, hover_text=custom_hover_text, rect_kws=dict(line=dict(color="grey", width=0.5)), ) # Plot track labels circos.text("count", r=bar_track.r_center, font=dict(color="orange")) circos.text("s1", r=track1.r_center, font=dict(color="red")) circos.text("s2", r=track2.r_center, font=dict(color="blue")) circos.text("s3", r=track3.r_center, font=dict(color="green")) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

   s1  s2  s3  count
A  44  20  28      6
B  47  80  34      5
C  64  69   0      5
D  67  79   0      7
E  67  47  36      5

Out[12]:

2. Large Tree¶

Example mammalian phylogenetic tree data is obtained from OrthoMaM.

2-1. Default Style¶

In [13]:

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

tree_file = load_example_tree_file("large_example.nwk")
circos, tv = Circos.initialize_from_tree(tree_file, leaf_label_size=5)
fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file tree_file = load_example_tree_file("large_example.nwk") circos, tv = Circos.initialize_from_tree(tree_file, leaf_label_size=5) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[13]:

2-2. Coloring Style¶

The legend is added with a dummy scatter. TODO Modify tree.py so instead of a shape simpleline a trace is drawed, with the legend associated.

In [14]:

import plotly.graph_objects as go

from pycirclizely import Circos
from pycirclizely.utils import ColorCycler, load_example_tree_file

tree_file = load_example_tree_file("large_example.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    start=-90,
    end=270,
    r_lim=(30, 100),
    leaf_label_size=5,
    ignore_branch_length=True,
    label_formatter=lambda t: t.replace("_", " "),
)

# Define group-species dict for tree annotation
# In this example, set minimum species list to specify group's MRCA node
group_name2species_list = dict(
    Monotremata=["Tachyglossus_aculeatus", "Ornithorhynchus_anatinus"],
    Marsupialia=["Monodelphis_domestica", "Vombatus_ursinus"],
    Xenarthra=["Choloepus_didactylus", "Dasypus_novemcinctus"],
    Afrotheria=["Trichechus_manatus", "Chrysochloris_asiatica"],
    Euarchontes=["Galeopterus_variegatus", "Theropithecus_gelada"],
    Glires=["Oryctolagus_cuniculus", "Microtus_oregoni"],
    Laurasiatheria=["Talpa_occidentalis", "Mirounga_leonina"],
)

# Set tree line color & label color
color_cycler = ColorCycler("T10")
group_name2color = {
    name: color_cycler.get_color() for name in group_name2species_list.keys()
}
for group_name, species_list in group_name2species_list.items():
    color = group_name2color[group_name]
    tv.set_node_line_props(species_list, apply_label_color=True, line=dict(color=color))

# Plot figure & set legend on center
fig = circos.plotfig()
for group_name, color in group_name2color.items():
    # Use a dummy trace to create a legend entry
    fig.add_trace(
        go.Scatter(
            x=[None],
            y=None,
            mode="markers",
            marker=dict(color=color, size=10),
            name=group_name,
            showlegend=True,
        )
    )

fig.update_layout(
    legend=dict(
        x=0.5,
        y=0.47,
        xanchor="center",
        yanchor="middle",
        font=dict(size=10),
        bgcolor="rgba(255,255,255,0.0)",
    )
)
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import plotly.graph_objects as go from pycirclizely import Circos from pycirclizely.utils import ColorCycler, load_example_tree_file tree_file = load_example_tree_file("large_example.nwk") circos, tv = Circos.initialize_from_tree( tree_file, start=-90, end=270, r_lim=(30, 100), leaf_label_size=5, ignore_branch_length=True, label_formatter=lambda t: t.replace("_", " "), ) # Define group-species dict for tree annotation # In this example, set minimum species list to specify group's MRCA node group_name2species_list = dict( Monotremata=["Tachyglossus_aculeatus", "Ornithorhynchus_anatinus"], Marsupialia=["Monodelphis_domestica", "Vombatus_ursinus"], Xenarthra=["Choloepus_didactylus", "Dasypus_novemcinctus"], Afrotheria=["Trichechus_manatus", "Chrysochloris_asiatica"], Euarchontes=["Galeopterus_variegatus", "Theropithecus_gelada"], Glires=["Oryctolagus_cuniculus", "Microtus_oregoni"], Laurasiatheria=["Talpa_occidentalis", "Mirounga_leonina"], ) # Set tree line color & label color color_cycler = ColorCycler("T10") group_name2color = { name: color_cycler.get_color() for name in group_name2species_list.keys() } for group_name, species_list in group_name2species_list.items(): color = group_name2color[group_name] tv.set_node_line_props(species_list, apply_label_color=True, line=dict(color=color)) # Plot figure & set legend on center fig = circos.plotfig() for group_name, color in group_name2color.items(): # Use a dummy trace to create a legend entry fig.add_trace( go.Scatter( x=[None], y=None, mode="markers", marker=dict(color=color, size=10), name=group_name, showlegend=True, ) ) fig.update_layout( legend=dict( x=0.5, y=0.47, xanchor="center", yanchor="middle", font=dict(size=10), bgcolor="rgba(255,255,255,0.0)", ) ) HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[14]:

2-3. With Heatmap¶

In [15]:

import numpy as np

from pycirclizely import Circos
from pycirclizely.utils import ColorCycler, load_example_tree_file

np.random.seed(0)

tree_file = load_example_tree_file("large_example.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    start=-350,
    end=0,
    r_lim=(10, 80),
    leaf_label_size=5,
    leaf_label_rmargin=23,
    line_kws=dict(line=dict(color="lightgrey", width=1.5)),
)
leaf_labels = tv.leaf_labels

# Define group-species dict for tree annotation
# In this example, set minimum species list to specify group's MRCA node
group_name2species_list = dict(
    Monotremata=["Tachyglossus_aculeatus", "Ornithorhynchus_anatinus"],
    Marsupialia=["Monodelphis_domestica", "Vombatus_ursinus"],
    Xenarthra=["Choloepus_didactylus", "Dasypus_novemcinctus"],
    Afrotheria=["Trichechus_manatus", "Chrysochloris_asiatica"],
    Euarchontes=["Galeopterus_variegatus", "Theropithecus_gelada"],
    Glires=["Oryctolagus_cuniculus", "Microtus_oregoni"],
    Laurasiatheria=["Talpa_occidentalis", "Mirounga_leonina"],
)

# Set tree line color
color_cycler = ColorCycler("Set2")
for species_list in group_name2species_list.values():
    tv.set_node_line_props(species_list, line=dict(color=color_cycler.get_color()))

# Plot heatmap
sector = circos.sectors[0]
heatmap_track = sector.add_track((80, 100))
matrix_data = np.random.randint(0, 100, (5, tv.leaf_num))
levels = list("EDCBA")
custom_hover_text = [
    f"""Leaf: {leaf_labels[col_idx]}
    <br>Level: {levels[row_idx]}
    <br>Value: {matrix_data[row_idx, col_idx]}"""
    for row_idx in range(matrix_data.shape[0])
    for col_idx in range(matrix_data.shape[1])
]
heatmap_track.heatmap(matrix_data, cmap="viridis", hover_text=custom_hover_text)
heatmap_track.yticks(
    [0.5, 1.5, 2.5, 3.5, 4.5],
    levels,
    vmax=5,
    tick_length=0,
    text_kws=dict(font=dict(size=10)),
)
fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import numpy as np from pycirclizely import Circos from pycirclizely.utils import ColorCycler, load_example_tree_file np.random.seed(0) tree_file = load_example_tree_file("large_example.nwk") circos, tv = Circos.initialize_from_tree( tree_file, start=-350, end=0, r_lim=(10, 80), leaf_label_size=5, leaf_label_rmargin=23, line_kws=dict(line=dict(color="lightgrey", width=1.5)), ) leaf_labels = tv.leaf_labels # Define group-species dict for tree annotation # In this example, set minimum species list to specify group's MRCA node group_name2species_list = dict( Monotremata=["Tachyglossus_aculeatus", "Ornithorhynchus_anatinus"], Marsupialia=["Monodelphis_domestica", "Vombatus_ursinus"], Xenarthra=["Choloepus_didactylus", "Dasypus_novemcinctus"], Afrotheria=["Trichechus_manatus", "Chrysochloris_asiatica"], Euarchontes=["Galeopterus_variegatus", "Theropithecus_gelada"], Glires=["Oryctolagus_cuniculus", "Microtus_oregoni"], Laurasiatheria=["Talpa_occidentalis", "Mirounga_leonina"], ) # Set tree line color color_cycler = ColorCycler("Set2") for species_list in group_name2species_list.values(): tv.set_node_line_props(species_list, line=dict(color=color_cycler.get_color())) # Plot heatmap sector = circos.sectors[0] heatmap_track = sector.add_track((80, 100)) matrix_data = np.random.randint(0, 100, (5, tv.leaf_num)) levels = list("EDCBA") custom_hover_text = [ f"""Leaf: {leaf_labels[col_idx]}
Level: {levels[row_idx]}
Value: {matrix_data[row_idx, col_idx]}""" for row_idx in range(matrix_data.shape[0]) for col_idx in range(matrix_data.shape[1]) ] heatmap_track.heatmap(matrix_data, cmap="viridis", hover_text=custom_hover_text) heatmap_track.yticks( [0.5, 1.5, 2.5, 3.5, 4.5], levels, vmax=5, tick_length=0, text_kws=dict(font=dict(size=10)), ) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[15]:

2-4. With Complex Heatmap¶

In [16]:

import numpy as np
import pandas as pd

from pycirclizely import Circos
from pycirclizely.utils import load_example_tree_file

np.random.seed(0)

tree_file = load_example_tree_file("large_example.nwk")
circos, tv = Circos.initialize_from_tree(
    tree_file,
    start=-355,
    end=-5,
    r_lim=(10, 80),
    leaf_label_size=0,
)
tv.track.axis(fillcolor="lightgrey", line=dict(color="lightgrey"), opacity=0.2)

# Create example dataframe for heatmap plot
heatmap_df = pd.DataFrame(
    dict(
        A=np.random.randint(0, 100, tv.leaf_num),
        B=np.random.randint(0, 100, tv.leaf_num),
        C=np.random.randint(0, 2, tv.leaf_num),
        D=np.random.randint(0, 2, tv.leaf_num).astype(bool),
    ),
    index=tv.leaf_labels,
)
print(heatmap_df)

# Plot heatmap with various style
sector = circos.sectors[0]
sector.rect(r_lim=(80, 100), line=dict(color="grey", width=1))

heatmap_track1 = sector.add_track((95, 100))
heatmap_track1.heatmap(
    heatmap_df["A"].to_numpy(),
    cmap="Reds",
    vmin=0,
    vmax=100,
    show_value=True,
    hover_text=None,
    text_kws=dict(font=dict(size=5), orientation="vertical"),
)
circos.text("A", r=heatmap_track1.r_center, font=dict(size=12, color="red"))

heatmap_track2 = sector.add_track((90, 95))
heatmap_track2.heatmap(
    heatmap_df["B"].to_numpy(), cmap="Blues", vmin=0, vmax=100, hover_text=None
)
circos.text("B", r=heatmap_track2.r_center, font=dict(size=12, color="blue"))

heatmap_track3 = sector.add_track((85, 90))
lime_cmap = [(0.0, "white"), (1.0, "lime")]
heatmap_track3.heatmap(
    heatmap_df["C"].to_numpy(),
    cmap=lime_cmap,
    vmin=0,
    vmax=1,
    show_value=True,
    hover_text=None,
    text_kws=dict(font=dict(size=5)),
    rect_kws=dict(line=dict(color="lightgrey", width=0.5)),
)
circos.text("C", r=heatmap_track3.r_center, font=dict(size=12, color="lime"))

heatmap_track4 = sector.add_track((80, 85))
orange_cmap = [(0.0, "white"), (1.0, "orange")]
heatmap_track4.heatmap(
    heatmap_df["D"].to_numpy(),
    cmap=orange_cmap,
    vmin=0,
    vmax=1,
    hover_text=None,
    rect_kws=dict(line=dict(color="lightgrey", width=0.5)),
)
circos.text("D", r=heatmap_track4.r_center, font=dict(size=12, color="orange"))

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import numpy as np import pandas as pd from pycirclizely import Circos from pycirclizely.utils import load_example_tree_file np.random.seed(0) tree_file = load_example_tree_file("large_example.nwk") circos, tv = Circos.initialize_from_tree( tree_file, start=-355, end=-5, r_lim=(10, 80), leaf_label_size=0, ) tv.track.axis(fillcolor="lightgrey", line=dict(color="lightgrey"), opacity=0.2) # Create example dataframe for heatmap plot heatmap_df = pd.DataFrame( dict( A=np.random.randint(0, 100, tv.leaf_num), B=np.random.randint(0, 100, tv.leaf_num), C=np.random.randint(0, 2, tv.leaf_num), D=np.random.randint(0, 2, tv.leaf_num).astype(bool), ), index=tv.leaf_labels, ) print(heatmap_df) # Plot heatmap with various style sector = circos.sectors[0] sector.rect(r_lim=(80, 100), line=dict(color="grey", width=1)) heatmap_track1 = sector.add_track((95, 100)) heatmap_track1.heatmap( heatmap_df["A"].to_numpy(), cmap="Reds", vmin=0, vmax=100, show_value=True, hover_text=None, text_kws=dict(font=dict(size=5), orientation="vertical"), ) circos.text("A", r=heatmap_track1.r_center, font=dict(size=12, color="red")) heatmap_track2 = sector.add_track((90, 95)) heatmap_track2.heatmap( heatmap_df["B"].to_numpy(), cmap="Blues", vmin=0, vmax=100, hover_text=None ) circos.text("B", r=heatmap_track2.r_center, font=dict(size=12, color="blue")) heatmap_track3 = sector.add_track((85, 90)) lime_cmap = [(0.0, "white"), (1.0, "lime")] heatmap_track3.heatmap( heatmap_df["C"].to_numpy(), cmap=lime_cmap, vmin=0, vmax=1, show_value=True, hover_text=None, text_kws=dict(font=dict(size=5)), rect_kws=dict(line=dict(color="lightgrey", width=0.5)), ) circos.text("C", r=heatmap_track3.r_center, font=dict(size=12, color="lime")) heatmap_track4 = sector.add_track((80, 85)) orange_cmap = [(0.0, "white"), (1.0, "orange")] heatmap_track4.heatmap( heatmap_df["D"].to_numpy(), cmap=orange_cmap, vmin=0, vmax=1, hover_text=None, rect_kws=dict(line=dict(color="lightgrey", width=0.5)), ) circos.text("D", r=heatmap_track4.r_center, font=dict(size=12, color="orange")) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

                            A   B  C      D
Tachyglossus_aculeatus     44  21  0  False
Ornithorhynchus_anatinus   47  25  1   True
Monodelphis_domestica      64  80  1   True
Gracilinanus_agilis        67  60  1   True
Dromiciops_gliroides       67  61  1  False
...                        ..  .. ..    ...
Halichoerus_grypus         75  72  1   True
Neomonachus_schauinslandi  56  61  1   True
Leptonychotes_weddellii    16  13  0   True
Mirounga_leonina           24   5  1   True
Mirounga_angustirostris    29   0  0  False

[190 rows x 4 columns]

Out[16]:

3. Multiple Trees¶

3-1. Default Style¶

In [17]:

import random

from Bio.Phylo.BaseTree import Tree

from pycirclizely import Circos

random.seed(0)

# Create 3 randomized trees
tree_size_list = [60, 40, 50]
trees = [Tree.randomized(size, branch_stdev=0.5) for size in tree_size_list]

# Initialize circos sector with 3 randomized tree size
sectors = {name: tree.count_terminals() for name, tree in zip(list("ABC"), trees)}
circos = Circos(sectors, space=5)

for sector, tree in zip(circos.sectors, trees):
    sector.text(f"{sector.name} ({sector.size})", r=120, font=dict(size=14))
    track = sector.add_track((30, 100))
    track.tree(tree, leaf_label_size=8)

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import random from Bio.Phylo.BaseTree import Tree from pycirclizely import Circos random.seed(0) # Create 3 randomized trees tree_size_list = [60, 40, 50] trees = [Tree.randomized(size, branch_stdev=0.5) for size in tree_size_list] # Initialize circos sector with 3 randomized tree size sectors = {name: tree.count_terminals() for name, tree in zip(list("ABC"), trees)} circos = Circos(sectors, space=5) for sector, tree in zip(circos.sectors, trees): sector.text(f"{sector.name} ({sector.size})", r=120, font=dict(size=14)) track = sector.add_track((30, 100)) track.tree(tree, leaf_label_size=8) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[17]:

3-2. With Heatmap + Bar¶

In [18]:

import random

import numpy as np
from Bio.Phylo.BaseTree import Tree

from pycirclizely import Circos

random.seed(0)
np.random.seed(0)

# Create 3 randomized trees
tree_size_list = [60, 40, 50]
trees = [Tree.randomized(size, branch_stdev=0.5) for size in tree_size_list]

# Initialize circos sector with 3 randomized tree size
sectors = {name: tree.count_terminals() for name, tree in zip(list("ABC"), trees)}
circos = Circos(sectors, space=5)

colors = ["tomato", "skyblue", "limegreen"]
cmaps = ["RdBu_r", "viridis", "Spectral"]
for sector, tree, color, cmap in zip(circos.sectors, trees, colors, cmaps):  # type: ignore[assignment]
    sector.text(f"{sector.name} ({sector.size})", font=dict(size=12))
    # Plot randomized tree
    tree_track = sector.add_track((30, 70))
    tree_track.axis(fillcolor=color, opacity=0.2)
    tree_track.tree(tree, leaf_label_size=0)
    # Plot randomized heatmap
    heatmap_track = sector.add_track((70, 85))
    matrix_data = np.random.randint(0, 100, (5, int(sector.size)))
    heatmap_track.axis(line=dict(color="grey"))
    heatmap_track.heatmap(matrix_data, cmap=cmap)
    # Plot randomized bar
    bar_track = sector.add_track((85, 100))
    x = np.arange(0, int(sector.size)) + 0.5
    height = np.random.randint(1, 10, int(sector.size))
    bar_track.bar(x, height, fillcolor=color, line=dict(color="grey", width=0.5))

fig = circos.plotfig()
HTML(pio.to_html(fig, include_plotlyjs="cdn"))

import random import numpy as np from Bio.Phylo.BaseTree import Tree from pycirclizely import Circos random.seed(0) np.random.seed(0) # Create 3 randomized trees tree_size_list = [60, 40, 50] trees = [Tree.randomized(size, branch_stdev=0.5) for size in tree_size_list] # Initialize circos sector with 3 randomized tree size sectors = {name: tree.count_terminals() for name, tree in zip(list("ABC"), trees)} circos = Circos(sectors, space=5) colors = ["tomato", "skyblue", "limegreen"] cmaps = ["RdBu_r", "viridis", "Spectral"] for sector, tree, color, cmap in zip(circos.sectors, trees, colors, cmaps): # type: ignore[assignment] sector.text(f"{sector.name} ({sector.size})", font=dict(size=12)) # Plot randomized tree tree_track = sector.add_track((30, 70)) tree_track.axis(fillcolor=color, opacity=0.2) tree_track.tree(tree, leaf_label_size=0) # Plot randomized heatmap heatmap_track = sector.add_track((70, 85)) matrix_data = np.random.randint(0, 100, (5, int(sector.size))) heatmap_track.axis(line=dict(color="grey")) heatmap_track.heatmap(matrix_data, cmap=cmap) # Plot randomized bar bar_track = sector.add_track((85, 100)) x = np.arange(0, int(sector.size)) + 0.5 height = np.random.randint(1, 10, int(sector.size)) bar_track.bar(x, height, fillcolor=color, line=dict(color="grey", width=0.5)) fig = circos.plotfig() HTML(pio.to_html(fig, include_plotlyjs="cdn"))

Out[18]:

In [ ]: