pyGenomeViz

Overview

pyGenomeViz is a genome visualization python package for comparative genomics. It is implemented based on matplotlib, the most popular visualization library in python, and can easily and beautifully plot genomic features and comparison results.

Installation

Install PyPI package:

pip install pygenomeviz

Install bioconda package:

conda install -c conda-forge -c bioconda pygenomeviz

Usage

Basic Usage

The example codes shown here are also available from jupyter notebook.

Single Genome Track Visualization

from pygenomeviz import GenomeViz

name, genome_size = "Tutorial 01", 5000
cds_list = ((100, 900, -1), (1100, 1300, 1), (1350, 1500, 1), (1520, 1700, 1), (1900, 2200, -1), (2500, 2700, 1), (2700, 2800, -1), (2850, 3000, -1), (3100, 3500, 1), (3600, 3800, -1), (3900, 4200, -1), (4300, 4700, -1), (4800, 4850, 1))

gv = GenomeViz()
track = gv.add_feature_track(name, genome_size)
for idx, cds in enumerate(cds_list, 1):
    start, end, strand = cds
    track.add_feature(start, end, strand, label=f"CDS{idx:02d}")

fig = gv.plotfig(dpi=100)

Multiple Genome Track & Link Visualization

from pygenomeviz import GenomeViz

genome_list = (
    {"name": "genome 01", "size": 1000, "cds_list": ((150, 300, 1), (500, 700, -1), (750, 950, 1))},
    {"name": "genome 02", "size": 1300, "cds_list": ((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))},
    {"name": "genome 03", "size": 1200, "cds_list": ((150, 300, 1), (350, 450, -1), (500, 700, -1), (701, 900, -1))},
)

gv = GenomeViz(tick_style="axis")
for genome in genome_list:
    name, size, cds_list = genome["name"], genome["size"], genome["cds_list"]
    track = gv.add_feature_track(name, size)
    for idx, cds in enumerate(cds_list, 1):
        start, end, strand = cds
        track.add_feature(start, end, strand, label=f"gene{idx:02d}", linewidth=1, labelrotation=0, labelvpos="top", labelhpos="center", labelha="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), normal_color="skyblue", inverted_color="lime")
gv.add_link(("genome 02", 350, 450), ("genome 03", 450, 350), normal_color="skyblue", inverted_color="lime")
gv.add_link(("genome 02", 900, 700), ("genome 03", 700, 500), normal_color="skyblue", inverted_color="lime")
gv.add_link(("genome 03", 900, 701), ("genome 02", 1150, 950), normal_color="skyblue", inverted_color="lime")

fig = gv.plotfig(dpi=100)

Practical Usage

The example codes shown here are also available from jupyter notebook.

Single Genome Track Visualization from Genbank file

from pygenomeviz import Genbank, GenomeViz, load_dataset

Multiple Genome Track & Link Visualization from Genbank files

from pygenomeviz import Genbank, GenomeViz, load_dataset

Customization Tips

Since pyGenomeViz is implemented based on matplotlib, users can easily customize the figure in the manner of matplotlib. Here are some tips for figure customization.

• Add GC content & GC skew subtrack
• Add annotation (Fill Box, ROI)
• Add colorbar (Experimetal implementation)