pycirclize带你轻松绘制基因组图

pip install pycirclize
conda install -c conda-forge pycirclize

from pycirclize import Circos
import numpy as np
np.random.seed(0)

sectors = {"A": 10, "B": 15, "C": 12, "D": 20, "E": 15}
circos = Circos(sectors, space=5)

for sector in circos.sectors:
    # Plot sector name
    sector.text(f"Sector: {sector.name}", r=110, size=15)
    # Create x positions & random y values
    x = np.arange(sector.start, sector.end) + 0.5
    y = np.random.randint(0, 100, len(x))
    # Plot lines
    track1 = sector.add_track((80, 100), r_pad_ratio=0.1)
    track1.xticks_by_interval(interval=1)
    track1.axis()
    track1.line(x, y)
    # Plot points 
    track2 = sector.add_track((55, 75), r_pad_ratio=0.1)
    track2.axis()
    track2.scatter(x, y)
    # Plot bars
    track3 = sector.add_track((30, 50), r_pad_ratio=0.1)
    track3.axis()
    track3.bar(x, y)

circos.link(("A", 0, 3), ("B", 15, 12))
circos.link(("B", 0, 3), ("C", 7, 11), color="skyblue")
circos.link(("C", 2, 5), ("E", 15, 12), color="chocolate", direction=1)
circos.link(("D", 3, 5), ("D", 18, 15), color="lime", ec="black", lw=0.5, hatch="//", direction=2)
circos.link(("D", 8, 10), ("E", 2, 8), color="violet", ec="red", lw=1.0, ls="dashed")

circos.savefig("example01.png")

from pycirclize import Circos
import pandas as pd

# Create matrix dataframe (3 x 6)
row_names = ["F1", "F2", "F3"]
col_names = ["T1", "T2", "T3", "T4", "T5", "T6"]
matrix_data = [
    [10, 16, 7, 7, 10, 8],
    [4, 9, 10, 12, 12, 7],
    [17, 13, 7, 4, 20, 4],
]
matrix_df = pd.DataFrame(matrix_data, index=row_names, columns=col_names)

# Initialize Circos from matrix for plotting Chord Diagram
circos = Circos.initialize_from_matrix(
    matrix_df,
    space=5,
    cmap="tab10",
    label_kws=dict(size=12),
    link_kws=dict(ec="black", lw=0.5, direction=1),
)

circos.savefig("example02.png")

from pycirclize import Circos
from pycirclize.parser import Gff
from pycirclize.utils import load_prokaryote_example_file

# Load GFF file
gff_file = load_prokaryote_example_file("enterobacteria_phage.gff")
gff = Gff(gff_file)

circos = Circos(sectors={gff.name: gff.range_size})
circos.text("Enterobacteria phage\n(NC_000902)", size=15)

sector = circos.sectors[0]
cds_track = sector.add_track((90, 100))
cds_track.axis(fc="#EEEEEE", ec="none")
# Plot forward CDS
cds_track.genomic_features(
    gff.extract_features("CDS", target_strand=1),
    plotstyle="arrow",
    r_lim=(95, 100),
    fc="salmon",
)
# Plot reverse CDS
cds_track.genomic_features(
    gff.extract_features("CDS", target_strand=-1),
    plotstyle="arrow",
    r_lim=(90, 95),
    fc="skyblue",
)
# Extract CDS product labels
pos_list, labels = [], []
for feat in gff.extract_features("CDS"):
    start, end = int(str(feat.location.end)), int(str(feat.location.start))
    pos = (start + end) / 2
    label = feat.qualifiers.get("product", [""])[0]
    if label == "" or label.startswith("hypothetical"):
        continue
    if len(label) > 20:
        label = label[:20] + "..."
    pos_list.append(pos)
    labels.append(label)
# Plot CDS product labels on outer position
cds_track.xticks(
    pos_list,
    labels,
    label_orientation="vertical",
    show_bottom_line=True,
    label_size=6,
    line_kws=dict(ec="grey"),
)
# Plot xticks & intervals on inner position
cds_track.xticks_by_interval(
    interval=5000,
    outer=False,
    show_bottom_line=True,
    label_formatter=lambda v: f"{v/ 1000:.1f} Kb",
    label_orientation="vertical",
    line_kws=dict(ec="grey"),
)

fig = circos.plotfig()

from pycirclize import Circos
from pycirclize.utils import load_eukaryote_example_dataset

# Load hg38 dataset (https://github.com/moshi4/pycirclize-data/tree/main/eukaryote/hg38)
chr_bed_file, cytoband_file, _ = load_eukaryote_example_dataset("hg38")

# Initialize Circos from BED chromosomes
circos = Circos.initialize_from_bed(chr_bed_file, space=3)
circos.text("Homo sapiens (hg38)", size=15)

# Add cytoband tracks from cytoband file
circos.add_cytoband_tracks((95, 100), cytoband_file)

# Plot chromosome name
for sector in circos.sectors:
    sector.text(sector.name, size=10)

fig = circos.plotfig()

from pycirclize import Circos
from pycirclize.utils import ColorCycler, load_eukaryote_example_dataset

# Load hg38 dataset (https://github.com/moshi4/pycirclize-data/tree/main/eukaryote/hg38)
chr_bed_file, cytoband_file, chr_links = load_eukaryote_example_dataset("hg38")

# Initialize Circos from BED chromosomes
circos = Circos.initialize_from_bed(chr_bed_file, space=3)
circos.text("Homo sapiens\n(hg38)", deg=315, r=150, size=12)

# Add cytoband tracks from cytoband file
circos.add_cytoband_tracks((95, 100), cytoband_file)

# Create chromosome color mapping
ColorCycler.set_cmap("hsv") 
chr_names = [s.name for s in circos.sectors]
colors = ColorCycler.get_color_list(len(chr_names))
chr_name2color = {name: color for name, color in zip(chr_names, colors)}

# Plot chromosome name & xticks
for sector in circos.sectors:
    sector.text(sector.name, r=120, size=10, color=chr_name2color[sector.name])
    sector.get_track("cytoband").xticks_by_interval(
        40000000,
        label_size=8,
        label_orientation="vertical",
        label_formatter=lambda v: f"{v / 1000000:.0f} Mb",
    )

# Plot chromosome link
for link in chr_links:
    region1 = (link.query_chr, link.query_start, link.query_end)
    region2 = (link.ref_chr, link.ref_start, link.ref_end)
    color = chr_name2color[link.query_chr]
    if link.query_chr in ("chr1", "chr8", "chr16") and link.query_chr != link.ref_chr:
        circos.link(region1, region2, color=color)

fig = circos.plotfig()