pyryotype 0.0.6

Draw an ideogram of either HG38 or CHM13 contigs in a matplotlib axes object.

pyryotype

---

Table of Contents

• pyryotype
  • Installation
  • Example usage
    • Coverage plotting
    • PAF plotting
  • License
  • Cytoband data

Installation

    pip install ideogram

Example usage

from pyryotype import GENOME, plot_ideogram
from matplotlib import pyplot as plt
fig, axes = plt.subplots(
    ncols=1,
    nrows=22,
    figsize=(11, 11),
    facecolor="white",
)
genome = GENOME.CHM13
for ax, contig_name in zip(axes, range(1, 23)):
    chromosome = f"chr{contig_name}"
    plot_ideogram(ax, target=chromosome, genome=genome)
fig.savefig("ideogram.png", dpi=300)

Will output:

Coverage plotting

Coverage plotting is designed to be used with the output of Mosdepth. The following example uses the output of mosdepth to plot the coverage of chromosome 1. The region representing the first 100Mb of the chromosome is highlighted in black.

from pathlib import Path
from matplotlib import pyplot as plt
from matplotlib.ticker import EngFormatter
import pandas as pd

from pyryotype.coverage import plot_coverage


test_cov_file = Path(__file__).parent / "static" / "chr1_cov.regions.bed.gz"

fig, ax = plt.subplots(
    ncols=1,
    nrows=1,
    figsize=(11, 2),
)
df = pd.read_csv(test_cov_file, sep="\t", names=["chromosome", "start", "end", "value"])
ax = plot_coverage(ax, df, "chr1", regions=[(0, 100000000)], ylabel="Coverage", color="black")
ax.set_xlabel("Genomic Position (bp)")

# ax.yaxis.set_visible(False)
ax.set_yticks([])
ax.set_yticklabels([])
for side in ("right", "top", "left"):
    ax.spines[side].set_visible(False)
formatter = EngFormatter(unit='b', places=1)
# Set formatter for the x-axis
ax.xaxis.set_major_formatter(formatter)

fig.savefig("example_outputs/test_coverage.png", dpi=300, bbox_inches="tight")

Will output something like:

PAF plotting

Designed primarily to plot the alignment of assemblies to a reference genome. Must provide a valid PAF file.

from matplotlib import pyplot as plt
from readpaf import parse_paf
from pathlib import Path
from pyryotype.paf_plotting import PAFProtocol, PlotMode, plot_paf_alignments
test_paf = Path(__file__).parent / "static" / "test.paf"
fig, ax = plt.subplots(
    ncols=1,
    nrows=1,
    figsize=(11, 1),
)

ax = plot_paf_alignments(
    ax,
    parse_paf(test_paf.open()),
    target="chr1",
    mapq_filter=0,
    strict=PlotMode.STRICT,
    contig_colours=PlotMode.UNIQUE_COLOURS,
)
ax.set_xlabel("")

# ax.yaxis.set_visible(False)
ax.set_yticks([])
ax.set_yticklabels([])
for side in ("right", "top", "left"):
    ax.spines[side].set_visible(False)
fig.savefig("tests/test_paf_plotting.png", dpi=300, bbox_inches="tight")

Will output the following image: The colours assigned to each alignment can be changed to either be based on the Alignment Strand, or unique for each record. See the PlotMode docstring for the options that can be applied.

Multiple mappings on the same chromosome can be collapsed into a single line by setting strict=PlotMode.STRICT. This can be seen in the above mappings, where the large block is comprised of 3 separate alignments, from the same read. IF strict=PlotMode.CHILL then each alignment will be plotted separately, even if these alignments are from the same read. This looks like:

License

pyryotype is distributed under the terms of the MIT license.

Cytoband data

• HG38 - Nushell, will have to be adapted for bash curl -L "https://hgdownload.cse.ucsc.edu/goldenpath/hg38/database/cytoBand.txt.gz" | gzip -d - | rg -Ne "^chr\\d+\t" | save cytoBand_HG38.tsv
• CHM13 - bash yay curl -L http://t2t.gi.ucsc.edu/chm13/hub/t2t-chm13-v2.0/download/chm13v2.0_cytobands_allchrs.bed.gz | gzip -d - > cytobands_chm13.bed