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#bioinformatics #comparative-genomics #genbank #genomics #genomics-visualization #gff #gff3 #matplotlib #microbial-genomics #microbiology #python #synteny #visualization

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HTML 4.7%

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README

pyGenomeViz

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/workflow.

For more information, please see full documentation here.

pygenomevizgallery.png Fig.1 pyGenomeViz example plot gallery

pygenomevizgui.gif Fig.2 pyGenomeViz web application example (Demo Page)

Installation

Python 3.10 or later is required for installation.

Install PyPI package:

pip install pygenomeviz

Install conda-forge package:

conda install -c conda-forge pygenomeviz

Use Docker (Image Registry):

docker run -it --rm -p 8501:8501 ghcr.io/moshi4/pygenomeviz:latest pgv-gui -h

API Examples

Jupyter notebooks containing code examples below is available here.

Features

from pygenomeviz import GenomeViz
gv = GenomeViz() gv.setscalexticks(ymargin=0.5)
track = gv.addfeaturetrack("track", 1000) track.add_sublabel()
Add features to track
track.add_feature(50, 200, 1)
track.add_feature(250, 460, -1, fc="blue")
track.add_feature(500, 710, 1, fc="lime", lw=1.0)
track.add_feature(750, 960, 1, fc="magenta", lw=1.0, ec="grey", hatch="//")
gv.savefig("features.png")

Styled Features

from pygenomeviz import GenomeViz
gv = GenomeViz() gv.setscalebar(ymargin=0.5)
track = gv.addfeaturetrack("track", (1000, 2000)) track.add_sublabel()
Add styled features
track.add_feature(1000, 1100, 1, label="arrow")
track.add_feature(1120, 1220, -1, plotstyle="bigarrow", label="bigarrow", fc="red", lw=1)
track.add_feature(1240, 1340, 1, plotstyle="box", label="box", fc="blue")
track.add_feature(1360, 1480, 1, plotstyle="bigbox", label="bigbox", fc="limegreen")
track.add_feature(1500, 1620, -1, plotstyle="rbox", label="rbox", fc="magenta", ec="blue", lw=1)
track.add_feature(1640, 1740, -1, plotstyle="bigrbox", label="bigrbox", fc="grey")
track.addfeature(1760, 1860, 1, fc="lime", hatch="o", arrowshaft_ratio=0.2, label="arrow shaft = 0.2")
track.addfeature(1880, 1980, 1, fc="lime", hatch="/", arrowshaft_ratio=1.0, label="arrow shaft = 1.0")
gv.savefig("styled_features.png")

styledfeatures.png

Tracks & Links

from pygenomeviz import GenomeViz
genome_list = [     ("genome 01", 1000, [(150, 300, 1), (500, 700, -1), (750, 950, 1)]),     ("genome 02", 1300, [(50, 200, 1), (350, 450, 1), (700, 900, -1), (950, 1150, -1)]),     ("genome 03", 1200, [(150, 300, 1), (350, 450, -1), (500, 700, -1), (700, 900, -1)]), ]
gv = GenomeViz(figtrackheight=0.7, trackaligntype="center") gv.setscalebar()
Set tracks & features
for genome in genome_list:
    name, size, features = genome[0], genome[1], genome[2]
    track = gv.addfeaturetrack(name, size)
    track.add_sublabel()
    for idx, feature in enumerate(features, 1):
        start, end, strand = feature
        track.addfeature(start, end, strand, plotstyle="bigarrow", lw=1, label=f"gene{idx:02d}", textkws=dict(rotation=0, vpos="top", hpos="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.addlink(("genome 02", 50, 200), ("genome 03", 150, 300), color="skyblue", invertedcolor="lime", curve=True)
gv.addlink(("genome 02", 350, 450), ("genome 03", 450, 350), color="skyblue", invertedcolor="lime", curve=True)
gv.addlink(("genome 02", 900, 700), ("genome 03", 700, 500), color="skyblue", invertedcolor="lime", curve=True)
gv.addlink(("genome 03", 900, 700), ("genome 02", 1150, 950), color="skyblue", invertedcolor="lime", curve=True)
gv.savefig("tracksandlinks.png")

tracksandlinks.png

Exon Features

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.addfeaturetrack("track", 5000)
Add exon features
track.addexonfeature(exonregions1, strand=1, plotstyle="box", label="box", textkws=dict(rotation=0, hpos="center"))
track.addexonfeature(exonregions2, strand=-1, plotstyle="arrow", label="arrow", textkws=dict(rotation=0, vpos="bottom", hpos="center"), patchkws=dict(fc="darkgrey"), intronpatch_kws=dict(ec="red"))
track.addexonfeature(exonregions3, strand=1, plotstyle="bigarrow", label="bigarrow", textkws=dict(rotation=0, hpos="center"), patch_kws=dict(fc="lime", lw=1))
gv.savefig("exon_features.png")

exonfeatures.png

Genbank Features

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import loadexamplegenbank_dataset
Parse Genbank file
gbkfiles = loadexamplegenbankdataset("yersinia_phage")
gbk = Genbank(gbk_files[0])
gv = GenomeViz(figtrackheight=0.7) gv.setscalebar(ymargin=0.5)
track = gv.addfeaturetrack(gbk.name, gbk.get_seqid2size())
for seg in track.segments:     # Plot CDS features     features = gbk.get_seqid2features()[seg.name]     seg.add_features(features, lw=0.5)     seg.add_sublabel()
gv.savefig("genbank_features.png")

genbankfeatures.png

GFF Features

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Gff
from pygenomeviz.utils import loadexamplegff_file
gfffile = loadexamplegfffile("escherichia_coli.gff.gz") gff = Gff(gff_file)
gv = GenomeViz() gv.setscalebar(ymargin=0.5)
target_ranges = ((215000, 230000), (300000, 320000)) track = gv.addfeaturetrack(name=gff.name, segments=target_ranges) track.setsegmentsep()
for segment in track.segments:     segment.add_sublabel()     features = gff.extractfeatures(featuretype=None, target_range=segment.range)     for feature in features:         if feature.type == "CDS":             segment.addfeatures(feature, labeltype="gene", fc="skyblue", lw=1.0, annotation=True, text_kws=dict(bbox=dict(boxstyle="round", fc="skyblue")))         elif feature.type == "rRNA":             segment.addfeatures(feature, labeltype="product", fc="lime", lw=1.0, hatch="//", annotation=True, text_kws=dict(bbox=dict(boxstyle="round", fc="lime")))
gv.savefig("gff_features.png")

gfffeatures.png

GFF Contigs

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Gff
from pygenomeviz.utils import loadexamplegfffile, ispseudo_feature
gfffile = loadexamplegfffile("mycoplasma_mycoides.gff") gff = Gff(gff_file)
gv = GenomeViz(figtrackheight=0.5, featuretrackratio=0.5) gv.setscalexticks(labelsize=10)
Plot CDS, rRNA features for each contig to tracks
for seqid, size in gff.get_seqid2size().items():
    track = gv.addfeaturetrack(seqid, size, labelsize=15)
    track.add_sublabel(size=10, color="grey")
    cdsfeatures = gff.getseqid2features(feature_type="CDS")[seqid]
    # CDS: blue, CDS(pseudo): grey
    for cdsfeature in cdsfeatures:
        color = "grey" if ispseudofeature(cds_feature) else "blue"
        track.addfeatures(cdsfeature, color=color)
    # rRNA: lime
    rrnafeatures = gff.getseqid2features(feature_type="rRNA")[seqid]
    track.addfeatures(rrnafeatures, color="lime")
gv.savefig("gff_contigs.png")

gffcontigs.png

Genbank Comparison by BLAST

from pygenomeviz import GenomeViz
from pygenomeviz.parser import Genbank
from pygenomeviz.utils import loadexamplegenbank_dataset
from pygenomeviz.align import Blast, AlignCoord
gbkfiles = loadexamplegenbankdataset("yersinia_phage") gbklist = list(map(Genbank, gbkfiles))
gv = GenomeViz(trackaligntype="center") gv.setscalebar()
Plot CDS features
for gbk in gbk_list:
    track = gv.addfeaturetrack(gbk.name, gbk.getseqid2size(), alignlabel=False)
    for seqid, features in gbk.get_seqid2features("CDS").items():
        segment = track.get_segment(seqid)
        segment.add_features(features, plotstyle="bigarrow", fc="limegreen", lw=0.5)
Run BLAST alignment & filter by user-defined threshold
aligncoords = Blast(gbklist, seqtype="protein").run()
aligncoords = AlignCoord.filter(aligncoords, lengththr=100, identitythr=30)
Plot BLAST alignment links
if len(align_coords) > 0:
    minident = int(min([ac.identity for ac in aligncoords if ac.identity]))
    color, inverted_color = "grey", "red"
    for ac in align_coords:
        gv.addlink(ac.querylink, ac.reflink, color=color, invertedcolor=invertedcolor, v=ac.identity, vmin=minident)
    gv.setcolorbar([color, invertedcolor], vmin=min_ident)
gv.savefig("genbankcomparisonby_blast.png")

genbankcomparisonbyblast.png

CLI Examples

pyGenomeViz provides CLI workflows for genome alignment result visualization of Genbank genomes using BLAST / MUMmer / MMseqs / progressiveMauve, respectively.

BLAST CLI Workflow

See pgv-blast document for details.

# Download example dataset
pgv-download yersinia_phage
Run BLAST CLI workflow
pgv-blast NC070914.gbk NC070915.gbk NC070916.gbk NC070918.gbk \
          -o pgv-blastexample --seqtype protein --showscale_bar --curve \
          --featurelinewidth 0.3 --lengththr 100 --identity_thr 30

pgv-blastexample2.png

MUMmer CLI Workflow

See pgv-mummer document for details.

# Download example dataset
pgv-download mycoplasma_mycoides
Run MUMmer CLI workflow
pgv-mummer GCF000023685.1.gbff GCF000800785.1.gbff GCF000959055.1.gbff GCF000959065.1.gbff \
           -o pgv-mummerexample --showscale_bar --curve \
           --feature_type2color CDS:blue rRNA:lime tRNA:magenta

pgv-mummerexample3.png

MMseqs CLI Workflow

See pgv-mmseqs document for details.

# Download example dataset
pgv-download enterobacteria_phage
Run MMseqs CLI workflow
pgv-mmseqs NC013600.gbk NC016566.gbk NC019724.gbk NC024783.gbk NC028901.gbk NC031081.gbk \
           -o pgv-mmseqsexample --showscalebar --curve --featurelinewidth 0.3 \
           --featuretype2color CDS:skyblue --normallinkcolor chocolate --invertedlink_color limegreen

pgv-mmseqsexample2.png

progressiveMauve CLI Workflow

See pgv-pmauve document for details.

# Download example dataset
pgv-download escherichia_coli
Run progressiveMauve CLI workflow
pgv-pmauve NC000913.gbk.gz NC002695.gbk.gz NC011751.gbk.gz NC011750.gbk.gz \
           -o pgv-pmauveexample --showscale_bar

pgv-pmauveexample1.png

GUI (Web Application)

pyGenomeViz implements GUI (Web Application) functionality using streamlit as an option. Users can easily visualize the genomic features in Genbank files and their comparison results with GUI (Demo Page). See pgv-gui document for details.

pygenomevizgui.gif

HTML Viewer

pyGenomeViz implements HTML viewer 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, pan/zoom, tooltip display, object color change, text change, etc are available in HTML viewer (Demo Page1, Demo Page2).

Following libraries were used to implement HTML viewer.

Spectrum: Colorpicker
Panzoom: SVG panning and zooming
Tabulator: Interactive Table
Micromodal: Modal dialog
Tippy.js: Tooltip

Inspiration

pyGenomeViz was inspired by

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.

pycirclizeexample.png Fig. pyCirclize example plot gallery