gene-loci-comparison 0.0.4

Create fancy (bokeh) gene locus plots from GenBank files

Gene Loci Comparison

Create fancy (bokeh) gene locus plots from GenBank files!

This repository extends the functionality of the excellent DnaFeaturesViewer

Setup

pip install git+https://github.com/MrTomRod/gene_loci_comparison.git

Examples

Bokeh

This library can also create interactive html/javascript-based plots. Open these files in your browser:

• single locus
• multiple loci with synchronized panning

Single locus, specify colors

from gene_loci_comparison import Locus, Loci
import matplotlib
import matplotlib.pyplot as plt

matplotlib.rcParams['font.family'] = "PT Sans Narrow"

locus = Locus(gbk_file='/path/to/file.gbk', locus_tag='FAM3257_001019')

locus_to_color = dict(
    FAM3257_001014='#1271c3',
    FAM3257_001015='#3171c3',
    FAM3257_001016='#5d71c3',
    FAM3257_001017='#9371c3',
    FAM3257_001018='#b171c3',
    FAM3257_001019='#cb71c3',
    FAM3257_001020='#ea71c3',
    FAM3257_001021='#fd71c3',
    # FAM3257_001021='#fd71c3'  # last gene: white (default color)
)

locus.colorize(locus_to_color)

ax, _ = locus.plot(figure_width=12)

plt.show()

Multiple loci

from gene_loci_comparison import Loci
import matplotlib

matplotlib.rcParams['font.family'] = "PT Sans Narrow"

# Each locus is made from a gbk-file, a gene identifier and a title (optional)
loci_of_interest = [
    dict(gbk='/path/to/file1.gbk', gene='FAM3257_00934', title='title1'),
    dict(gbk='/path/to/file2.gbk', gene='FAM3257_000019', title='title2'),
    dict(gbk='/path/to/file3.gbk', gene='FAM3257_001020', title='title3'),
]

# Highlight selected genes
locus_to_color_dict = {locus['gene']: '#1984ff' for locus in loci_of_interest}

# Generate loci object
loci = Loci.generate(
    loci_of_interest,
    locus_to_color_dict=locus_to_color_dict
)

plot = loci.plot(auto_reverse=False)

plot.show()

Multiple loci, autoreversed

To automatically reverse loci based on the direction of the selected genes. Simply set auto_reverse to True.

Multiple loci, with GC content

Change plotting method from plot_multiple to plot_multiple_gc.

plot = loci.plot_gc(
    auto_reverse=True,
    window_bp=200
)