# pyGenomeViz
[](https://pypi.python.org/pypi/pygenomeviz)
[](https://anaconda.org/bioconda/pygenomeviz)
[](https://github.com/moshi4/pyGenomeViz/actions/workflows/ci.yml)
## Table of contents
- [Overview](#overview)
- [Installation](#installation)
- [API Examples](#api-examples)
- [CLI Examples](#cli-examples)
- [GUI (Web Application)](#gui-web-application)
- [Interactive HTML Viewer](#interactive-html-viewer)
- [Inspiration](#inspiration)
- [Circular Genome Visualization](#circular-genome-visualization)
## Overview
pyGenomeViz is a genome visualization python package for comparative genomics implemented based on matplotlib.
This package is developed for the purpose of easily and beautifully plotting genomic
features and sequence similarity comparison links between multiple genomes.
It supports genome visualization of Genbank/GFF format file and can be saved figure in various formats (JPG/PNG/SVG/PDF/HTML).
User can use pyGenomeViz for interactive genome visualization figure plotting on jupyter notebook,
or automatic genome visualization figure plotting in genome analysis scripts/pipelines.
For more information, please see full documentation [here](https://moshi4.github.io/pyGenomeViz/).
**Fig.1 pyGenomeViz example plot gallery**
:sparkles: GUI (Web Application) functionality is newly added from v0.4.0
**Fig.2 pyGenomeViz web application example ([Demo Page](https://pygenomeviz.streamlit.app))**
## Installation
`Python 3.8 or later` is required for installation.
**Install PyPI package:**
pip install pygenomeviz
**Install bioconda package:**
conda install -c conda-forge -c bioconda pygenomeviz
**Use Docker ([Image Registry](https://github.com/moshi4/pyGenomeViz/pkgs/container/pygenomeviz)):**
Case1. Run CLI Workflow:
docker run -it --rm ghcr.io/moshi4/pygenomeviz:latest pgv-mummer -h
Case2. Launch GUI (Web Application):
docker run -it --rm -p 8501:8501 ghcr.io/moshi4/pygenomeviz:latest pgv-gui
## API Examples
Jupyter notebooks containing code examples below is available [here](https://moshi4.github.io/pyGenomeViz/getting_started/).
### Basic Example
#### Single Track
```python
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}")
gv.savefig("example01.png")
```
#### Multiple Tracks & Links
```python
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), (700, 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", curve=True)
gv.add_link(("genome 02", 350, 450), ("genome 03", 450, 350), normal_color="skyblue", inverted_color="lime", curve=True)
gv.add_link(("genome 02", 900, 700), ("genome 03", 700, 500), normal_color="skyblue", inverted_color="lime", curve=True)
gv.add_link(("genome 03", 900, 700), ("genome 02", 1150, 950), normal_color="skyblue", inverted_color="lime", curve=True)
gv.savefig("example02.png")
```
#### Exon Features
```python
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(name=f"Exon Features", size=5000)
track.add_exon_feature(exon_regions1, strand=1, plotstyle="box", label="box", labelrotation=0, labelha="center")
track.add_exon_feature(exon_regions2, strand=-1, plotstyle="arrow", label="arrow", labelrotation=0, labelha="center", facecolor="darkgrey", intron_patch_kws={"ec": "red"})
exon_labels = [f"exon{i+1}" for i in range(len(exon_regions3))]
track.add_exon_feature(exon_regions3, strand=1, plotstyle="bigarrow", label="bigarrow", facecolor="lime", linewidth=1, exon_labels=exon_labels, labelrotation=0, labelha="center", exon_label_kws={"y": 0, "va": "center", "color": "blue"})
gv.savefig("example03.png")
```
### Practical Example
#### Add Features from Genbank file
```python
from pygenomeviz import Genbank, GenomeViz, load_example_dataset
gbk_files, _ = load_example_dataset("enterobacteria_phage")
gbk = Genbank(gbk_files[0])
gv = GenomeViz()
track = gv.add_feature_track(gbk.name, gbk.range_size)
track.add_genbank_features(gbk)
gv.savefig("example04.png")
```
#### Add Features from GFF file
```python
from pygenomeviz import Gff, GenomeViz, load_example_gff
gff_file = load_example_gff("enterobacteria_phage.gff")
gff = Gff(gff_file, min_range=5000, max_range=25000)
gv = GenomeViz(fig_track_height=0.7, tick_track_ratio=0.5, tick_style="bar")
track = gv.add_feature_track(gff.name, size=gff.range_size, start_pos=gff.min_range)
track.add_gff_features(gff, plotstyle="arrow", facecolor="tomato")
track.set_sublabel()
gv.savefig("example05.png")
```
#### Multiple Tracks & Links from Genbank files
```python
from pygenomeviz import Genbank, GenomeViz, load_example_dataset
gv = GenomeViz(
fig_track_height=0.7,
feature_track_ratio=0.2,
tick_track_ratio=0.4,
tick_style="bar",
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, facecolor="limegreen", linewidth=0.5, arrow_shaft_ratio=1.0)
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, curve=True)
gv.savefig("example06.png")
```
### 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.
#### Customization Tips 01
- Add `GC Content` & `GC skew` subtrack
- Add annotation label & fillbox
- Add colorbar for links identity
<details>
<summary>Code</summary>
```python
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, name="gc_content")
gv.top_track.add_subtrack(ratio=0.7, name="gc_skew")
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 coloarbar for link
gv.set_colorbar(fig, vmin=min_identity)
fig.savefig("example07.png")
```
</details>
#### Customization Tips 02
- Add legends
- Add colorbar for links identity
<details>
<summary>Code</summary>
```python
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=0.3,
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,
)
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_label="Identity", bar_labelsize=10)
fig.savefig("example08.png")
```
</details>
## CLI Examples
pyGenomeViz provides CLI workflow for visualization of genome alignment or
reciprocal best-hit CDS search results with `MUMmer` or `MMseqs` or `progressiveMauve`.
Each CLI workflow requires the installation of additional dependent tools to run.
### MUMmer CLI Workflow Example
See [pgv-mummer document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-mummer/) for details.
Download example dataset: `pgv-download-dataset -n erwinia_phage`
> :warning: MUMmer must be installed in advance to run
pgv-mummer --gbk_resources MT939486.gbk MT939487.gbk MT939488.gbk LT960552.gbk \
-o mummer_example --tick_style axis --align_type left --feature_plotstyle arrow
### MMseqs CLI Workflow Example
See [pgv-mmseqs document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-mmseqs/) for details.
Download example dataset: `pgv-download-dataset -n enterobacteria_phage`
> :warning: MMseqs must be installed in advance to run
pgv-mmseqs --gbk_resources NC_019724.gbk NC_024783.gbk NC_016566.gbk NC_013600.gbk NC_031081.gbk NC_028901.gbk \
-o mmseqs_example --fig_track_height 0.7 --feature_linewidth 0.3 --tick_style bar --curve \
--normal_link_color chocolate --inverted_link_color limegreen --feature_color skyblue
### progressiveMauve CLI Workflow Example
See [pgv-pmauve document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-pmauve/) for details.
Download example dataset: `pgv-download-dataset -n escherichia_coli`
> :warning: progressiveMauve must be installed in advance to run
pgv-pmauve --seq_files NC_000913.gbk NC_002695.gbk NC_011751.gbk NC_011750.gbk \
-o pmauve_example --tick_style bar
## GUI (Web Application)
pyGenomeViz implements GUI (Web Application) functionality using [streamlit](https://github.com/streamlit/streamlit) as an option ([Demo Page](https://pygenomeviz.streamlit.app)).
Users can easily visualize the genome data of Genbank files and their comparison results with GUI.
See [pgv-gui document](https://moshi4.github.io/pyGenomeViz/gui-docs/pgv-gui/) for details.
## Interactive HTML Viewer
pyGenomeViz implements HTML file output functionality for interactive data visualization.
In API, HTML file can be output using `savefig_html` method. In CLI, user can select HTML file output option.
As shown below, data tooltip display, pan/zoom, object color change, text change, etc are available in HTML viewer
([Demo Page](https://moshi4.github.io/pyGenomeViz/images/pgv-viewer-demo.html)).
## Inspiration
pyGenomeViz was inspired by
- [GenomeDiagram (BioPython)](https://github.com/biopython/biopython)
- [Easyfig](http://mjsull.github.io/Easyfig/)
- [genoplotR](https://genoplotr.r-forge.r-project.org/)
- [gggenomes](https://github.com/thackl/gggenomes)
## Circular Genome Visualization
pyGenomeViz is a python package designed for linear genome visualization.
If you are interested in circular genome visualization, check out my other python package [pyCirclize](https://github.com/moshi4/pyCirclize).
**Fig. pyCirclize example plot gallery**
Raw data
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"description": "# pyGenomeViz\n\n\n\n\n[](https://pypi.python.org/pypi/pygenomeviz)\n[](https://anaconda.org/bioconda/pygenomeviz)\n[](https://github.com/moshi4/pyGenomeViz/actions/workflows/ci.yml)\n\n## Table of contents\n\n- [Overview](#overview)\n- [Installation](#installation)\n- [API Examples](#api-examples)\n- [CLI Examples](#cli-examples)\n- [GUI (Web Application)](#gui-web-application)\n- [Interactive HTML Viewer](#interactive-html-viewer)\n- [Inspiration](#inspiration)\n- [Circular Genome Visualization](#circular-genome-visualization)\n\n## Overview\n\npyGenomeViz is a genome visualization python package for comparative genomics implemented based on matplotlib.\nThis package is developed for the purpose of easily and beautifully plotting genomic\nfeatures and sequence similarity comparison links between multiple genomes.\nIt supports genome visualization of Genbank/GFF format file and can be saved figure in various formats (JPG/PNG/SVG/PDF/HTML).\nUser can use pyGenomeViz for interactive genome visualization figure plotting on jupyter notebook,\nor automatic genome visualization figure plotting in genome analysis scripts/pipelines.\n\nFor more information, please see full documentation [here](https://moshi4.github.io/pyGenomeViz/).\n\n \n**Fig.1 pyGenomeViz example plot gallery**\n\n:sparkles: GUI (Web Application) functionality is newly added from v0.4.0\n\n\n**Fig.2 pyGenomeViz web application example ([Demo Page](https://pygenomeviz.streamlit.app))**\n\n## Installation\n\n`Python 3.8 or later` is required for installation.\n\n**Install PyPI package:**\n\n pip install pygenomeviz\n\n**Install bioconda package:**\n\n conda install -c conda-forge -c bioconda pygenomeviz\n\n**Use Docker ([Image Registry](https://github.com/moshi4/pyGenomeViz/pkgs/container/pygenomeviz)):**\n\nCase1. Run CLI Workflow:\n\n docker run -it --rm ghcr.io/moshi4/pygenomeviz:latest pgv-mummer -h\n\nCase2. Launch GUI (Web Application):\n\n docker run -it --rm -p 8501:8501 ghcr.io/moshi4/pygenomeviz:latest pgv-gui\n\n## API Examples\n\nJupyter notebooks containing code examples below is available [here](https://moshi4.github.io/pyGenomeViz/getting_started/).\n\n### Basic Example\n\n#### Single Track\n\n```python\nfrom pygenomeviz import GenomeViz\n\nname, genome_size = \"Tutorial 01\", 5000\ncds_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))\n\ngv = GenomeViz()\ntrack = gv.add_feature_track(name, genome_size)\nfor idx, cds in enumerate(cds_list, 1):\n start, end, strand = cds\n track.add_feature(start, end, strand, label=f\"CDS{idx:02d}\")\n\ngv.savefig(\"example01.png\")\n```\n\n\n\n#### Multiple Tracks & Links\n\n```python\nfrom pygenomeviz import GenomeViz\n\ngenome_list = (\n {\"name\": \"genome 01\", \"size\": 1000, \"cds_list\": ((150, 300, 1), (500, 700, -1), (750, 950, 1))},\n {\"name\": \"genome 02\", \"size\": 1300, \"cds_list\": ((50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1))},\n {\"name\": \"genome 03\", \"size\": 1200, \"cds_list\": ((150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1))},\n)\n\ngv = GenomeViz(tick_style=\"axis\")\nfor genome in genome_list:\n name, size, cds_list = genome[\"name\"], genome[\"size\"], genome[\"cds_list\"]\n track = gv.add_feature_track(name, size)\n for idx, cds in enumerate(cds_list, 1):\n start, end, strand = cds\n track.add_feature(start, end, strand, label=f\"gene{idx:02d}\", linewidth=1, labelrotation=0, labelvpos=\"top\", labelhpos=\"center\", labelha=\"center\")\n\n# Add links between \"genome 01\" and \"genome 02\"\ngv.add_link((\"genome 01\", 150, 300), (\"genome 02\", 50, 200))\ngv.add_link((\"genome 01\", 700, 500), (\"genome 02\", 900, 700))\ngv.add_link((\"genome 01\", 750, 950), (\"genome 02\", 1150, 950))\n# Add links between \"genome 02\" and \"genome 03\"\ngv.add_link((\"genome 02\", 50, 200), (\"genome 03\", 150, 300), normal_color=\"skyblue\", inverted_color=\"lime\", curve=True)\ngv.add_link((\"genome 02\", 350, 450), (\"genome 03\", 450, 350), normal_color=\"skyblue\", inverted_color=\"lime\", curve=True)\ngv.add_link((\"genome 02\", 900, 700), (\"genome 03\", 700, 500), normal_color=\"skyblue\", inverted_color=\"lime\", curve=True)\ngv.add_link((\"genome 03\", 900, 700), (\"genome 02\", 1150, 950), normal_color=\"skyblue\", inverted_color=\"lime\", curve=True)\n\ngv.savefig(\"example02.png\")\n```\n\n\n\n#### Exon Features\n\n```python\nfrom pygenomeviz import GenomeViz\n\nexon_regions1 = [(0, 210), (300, 480), (590, 800), (850, 1000), (1030, 1300)]\nexon_regions2 = [(1500, 1710), (2000, 2480), (2590, 2800)]\nexon_regions3 = [(3000, 3300), (3400, 3690), (3800, 4100), (4200, 4620)]\n\ngv = GenomeViz()\ntrack = gv.add_feature_track(name=f\"Exon Features\", size=5000)\ntrack.add_exon_feature(exon_regions1, strand=1, plotstyle=\"box\", label=\"box\", labelrotation=0, labelha=\"center\")\ntrack.add_exon_feature(exon_regions2, strand=-1, plotstyle=\"arrow\", label=\"arrow\", labelrotation=0, labelha=\"center\", facecolor=\"darkgrey\", intron_patch_kws={\"ec\": \"red\"})\n\nexon_labels = [f\"exon{i+1}\" for i in range(len(exon_regions3))]\ntrack.add_exon_feature(exon_regions3, strand=1, plotstyle=\"bigarrow\", label=\"bigarrow\", facecolor=\"lime\", linewidth=1, exon_labels=exon_labels, labelrotation=0, labelha=\"center\", exon_label_kws={\"y\": 0, \"va\": \"center\", \"color\": \"blue\"})\n\ngv.savefig(\"example03.png\")\n```\n\n\n\n### Practical Example\n\n#### Add Features from Genbank file\n\n```python\nfrom pygenomeviz import Genbank, GenomeViz, load_example_dataset\n\ngbk_files, _ = load_example_dataset(\"enterobacteria_phage\")\ngbk = Genbank(gbk_files[0])\n\ngv = GenomeViz()\ntrack = gv.add_feature_track(gbk.name, gbk.range_size)\ntrack.add_genbank_features(gbk)\n\ngv.savefig(\"example04.png\")\n```\n\n\n\n#### Add Features from GFF file\n\n```python\nfrom pygenomeviz import Gff, GenomeViz, load_example_gff\n\ngff_file = load_example_gff(\"enterobacteria_phage.gff\")\ngff = Gff(gff_file, min_range=5000, max_range=25000)\n\ngv = GenomeViz(fig_track_height=0.7, tick_track_ratio=0.5, tick_style=\"bar\")\ntrack = gv.add_feature_track(gff.name, size=gff.range_size, start_pos=gff.min_range)\ntrack.add_gff_features(gff, plotstyle=\"arrow\", facecolor=\"tomato\")\ntrack.set_sublabel()\n\ngv.savefig(\"example05.png\")\n```\n\n\n\n#### Multiple Tracks & Links from Genbank files\n\n```python\nfrom pygenomeviz import Genbank, GenomeViz, load_example_dataset\n\ngv = GenomeViz(\n fig_track_height=0.7,\n feature_track_ratio=0.2,\n tick_track_ratio=0.4,\n tick_style=\"bar\",\n align_type=\"center\",\n)\n\ngbk_files, links = load_example_dataset(\"escherichia_phage\")\nfor gbk_file in gbk_files:\n gbk = Genbank(gbk_file)\n track = gv.add_feature_track(gbk.name, gbk.range_size)\n track.add_genbank_features(gbk, facecolor=\"limegreen\", linewidth=0.5, arrow_shaft_ratio=1.0)\n\nfor link in links:\n link_data1 = (link.ref_name, link.ref_start, link.ref_end)\n link_data2 = (link.query_name, link.query_start, link.query_end)\n gv.add_link(link_data1, link_data2, v=link.identity, curve=True)\n\ngv.savefig(\"example06.png\")\n```\n\n\n\n### Customization Tips\n\nSince pyGenomeViz is implemented based on matplotlib, users can easily customize\nthe figure in the manner of matplotlib. Here are some tips for figure customization.\n\n#### Customization Tips 01\n\n- Add `GC Content` & `GC skew` subtrack\n- Add annotation label & fillbox\n- Add colorbar for links identity\n\n<details>\n<summary>Code</summary>\n\n```python\nfrom pygenomeviz import Genbank, GenomeViz, load_example_dataset\n\ngv = GenomeViz(\n fig_width=12,\n fig_track_height=0.7,\n feature_track_ratio=0.5,\n tick_track_ratio=0.3,\n tick_style=\"axis\",\n tick_labelsize=10,\n)\n\ngbk_files, links = load_example_dataset(\"erwinia_phage\")\ngbk_list = [Genbank(gbk_file) for gbk_file in gbk_files]\nfor gbk in gbk_list:\n track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=15)\n track.add_genbank_features(gbk, plotstyle=\"arrow\")\n\nmin_identity = int(min(link.identity for link in links))\nfor link in links:\n link_data1 = (link.ref_name, link.ref_start, link.ref_end)\n link_data2 = (link.query_name, link.query_start, link.query_end)\n gv.add_link(link_data1, link_data2, v=link.identity, vmin=min_identity)\n\n# Add subtracks to top track for plotting 'GC content' & 'GC skew'\ngv.top_track.add_subtrack(ratio=0.7, name=\"gc_content\")\ngv.top_track.add_subtrack(ratio=0.7, name=\"gc_skew\")\n\nfig = gv.plotfig()\n\n# Add label annotation to top track\ntop_track = gv.top_track # or, gv.get_track(\"MT939486\") or gv.get_tracks()[0]\nlabel, start, end = \"Inverted\", 310000 + top_track.offset, 358000 + top_track.offset\ncenter = int((start + end) / 2)\ntop_track.ax.hlines(1.5, start, end, colors=\"red\", linewidth=1, linestyles=\"dashed\", clip_on=False)\ntop_track.ax.text(center, 2.0, label, fontsize=12, color=\"red\", ha=\"center\", va=\"bottom\")\n\n# Add fillbox to top track\nx, y = (start, start, end, end), (1, -1, -1, 1)\ntop_track.ax.fill(x, y, fc=\"lime\", linewidth=0, alpha=0.1, zorder=-10)\n\n# Plot GC content for top track\npos_list, gc_content_list = gbk_list[0].calc_gc_content()\npos_list += gv.top_track.offset # Offset is required if align_type is not 'left'\ngc_content_ax = gv.top_track.subtracks[0].ax\ngc_content_ax.set_ylim(bottom=0, top=max(gc_content_list))\ngc_content_ax.fill_between(pos_list, gc_content_list, alpha=0.2, color=\"blue\")\ngc_content_ax.text(gv.top_track.offset, max(gc_content_list) / 2, \"GC(%) \", ha=\"right\", va=\"center\", color=\"blue\")\n\n# Plot GC skew for top track\npos_list, gc_skew_list = gbk_list[0].calc_gc_skew()\npos_list += gv.top_track.offset # Offset is required if align_type is not 'left'\ngc_skew_abs_max = max(abs(gc_skew_list))\ngc_skew_ax = gv.top_track.subtracks[1].ax\ngc_skew_ax.set_ylim(bottom=-gc_skew_abs_max, top=gc_skew_abs_max)\ngc_skew_ax.fill_between(pos_list, gc_skew_list, alpha=0.2, color=\"red\")\ngc_skew_ax.text(gv.top_track.offset, 0, \"GC skew \", ha=\"right\", va=\"center\", color=\"red\")\n\n# Set coloarbar for link\ngv.set_colorbar(fig, vmin=min_identity)\n\nfig.savefig(\"example07.png\")\n```\n\n</details>\n\n\n\n#### Customization Tips 02\n\n- Add legends\n- Add colorbar for links identity\n\n<details>\n<summary>Code</summary>\n\n```python\nfrom matplotlib.lines import Line2D\nfrom matplotlib.patches import Patch\n\nfrom pygenomeviz import Genbank, GenomeViz, load_example_dataset\n\ngv = GenomeViz(\n fig_width=10,\n fig_track_height=0.5,\n feature_track_ratio=0.5,\n tick_track_ratio=0.3,\n align_type=\"center\",\n tick_style=\"bar\",\n tick_labelsize=10,\n)\n\ngbk_files, links = load_example_dataset(\"enterobacteria_phage\")\nfor idx, gbk_file in enumerate(gbk_files):\n gbk = Genbank(gbk_file)\n track = gv.add_feature_track(gbk.name, gbk.range_size, labelsize=10)\n track.add_genbank_features(\n gbk,\n label_type=\"product\" if idx == 0 else None, # Labeling only top track\n label_handle_func=lambda s: \"\" if s.startswith(\"hypothetical\") else s, # Ignore 'hypothetical ~~~' label\n labelsize=8,\n labelvpos=\"top\",\n facecolor=\"skyblue\",\n linewidth=0.5,\n )\n\nnormal_color, inverted_color, alpha = \"chocolate\", \"limegreen\", 0.5\nmin_identity = int(min(link.identity for link in links))\nfor link in links:\n link_data1 = (link.ref_name, link.ref_start, link.ref_end)\n link_data2 = (link.query_name, link.query_start, link.query_end)\n gv.add_link(link_data1, link_data2, normal_color, inverted_color, alpha, v=link.identity, vmin=min_identity, curve=True)\n\nfig = gv.plotfig()\n\n# Add Legends (Maybe there is a better way)\nhandles = [\n Line2D([], [], marker=\">\", color=\"skyblue\", label=\"CDS\", ms=10, ls=\"none\"),\n Patch(color=normal_color, label=\"Normal Link\"),\n Patch(color=inverted_color, label=\"Inverted Link\"),\n]\nfig.legend(handles=handles, bbox_to_anchor=(1, 1))\n\n# Set colorbar for link\ngv.set_colorbar(fig, bar_colors=[normal_color, inverted_color], alpha=alpha, vmin=min_identity, bar_label=\"Identity\", bar_labelsize=10)\n\nfig.savefig(\"example08.png\")\n```\n\n</details>\n\n\n\n## CLI Examples\n\npyGenomeViz provides CLI workflow for visualization of genome alignment or\nreciprocal best-hit CDS search results with `MUMmer` or `MMseqs` or `progressiveMauve`.\nEach CLI workflow requires the installation of additional dependent tools to run.\n\n### MUMmer CLI Workflow Example\n\nSee [pgv-mummer document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-mummer/) for details.\n\nDownload example dataset: `pgv-download-dataset -n erwinia_phage`\n\n> :warning: MUMmer must be installed in advance to run\n\n pgv-mummer --gbk_resources MT939486.gbk MT939487.gbk MT939488.gbk LT960552.gbk \\\n -o mummer_example --tick_style axis --align_type left --feature_plotstyle arrow\n\n \n\n### MMseqs CLI Workflow Example\n\nSee [pgv-mmseqs document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-mmseqs/) for details.\n\nDownload example dataset: `pgv-download-dataset -n enterobacteria_phage`\n\n> :warning: MMseqs must be installed in advance to run\n\n pgv-mmseqs --gbk_resources NC_019724.gbk NC_024783.gbk NC_016566.gbk NC_013600.gbk NC_031081.gbk NC_028901.gbk \\\n -o mmseqs_example --fig_track_height 0.7 --feature_linewidth 0.3 --tick_style bar --curve \\\n --normal_link_color chocolate --inverted_link_color limegreen --feature_color skyblue\n\n \n\n### progressiveMauve CLI Workflow Example\n\nSee [pgv-pmauve document](https://moshi4.github.io/pyGenomeViz/cli-docs/pgv-pmauve/) for details.\n\nDownload example dataset: `pgv-download-dataset -n escherichia_coli`\n\n> :warning: progressiveMauve must be installed in advance to run\n\n pgv-pmauve --seq_files NC_000913.gbk NC_002695.gbk NC_011751.gbk NC_011750.gbk \\\n -o pmauve_example --tick_style bar\n\n \n\n## GUI (Web Application)\n\npyGenomeViz implements GUI (Web Application) functionality using [streamlit](https://github.com/streamlit/streamlit) as an option ([Demo Page](https://pygenomeviz.streamlit.app)).\nUsers can easily visualize the genome data of Genbank files and their comparison results with GUI.\nSee [pgv-gui document](https://moshi4.github.io/pyGenomeViz/gui-docs/pgv-gui/) for details.\n\n\n\n## Interactive HTML Viewer\n\npyGenomeViz implements HTML file output functionality for interactive data visualization.\nIn API, HTML file can be output using `savefig_html` method. In CLI, user can select HTML file output option.\nAs shown below, data tooltip display, pan/zoom, object color change, text change, etc are available in HTML viewer\n([Demo Page](https://moshi4.github.io/pyGenomeViz/images/pgv-viewer-demo.html)).\n\n\n\n## Inspiration\n\npyGenomeViz was inspired by\n\n- [GenomeDiagram (BioPython)](https://github.com/biopython/biopython)\n- [Easyfig](http://mjsull.github.io/Easyfig/)\n- [genoplotR](https://genoplotr.r-forge.r-project.org/)\n- [gggenomes](https://github.com/thackl/gggenomes)\n\n## Circular Genome Visualization\n\npyGenomeViz is a python package designed for linear genome visualization.\nIf you are interested in circular genome visualization, check out my other python package [pyCirclize](https://github.com/moshi4/pyCirclize).\n\n \n**Fig. pyCirclize example plot gallery**\n",
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