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Project Description

Dna Features Viewer is a Python library to (wait for it…) visualize DNA features, e.g. from GenBank or Gff files, using the plotting library Matplotlib:

Dna Features Viewer is fairly minimal (<200 lines of code) but can display sequences with lots of overlapping features and long labels, without getting too messy. The plots can be output to many different formats (PNG, JPEG, SVG, PDF).

License

Dna Features Viewer is an open-source software originally written at the Edinburgh Genome Foundry by Zulko and released under the MIT licence. Everyone is welcome to contribute !

Installation

Dna Features Viewer can be installed by unzipping the source code in one directory and using this command:

sudo python setup.py install

PIP install is coming soon !

Examples of use

Defining the features by hand

In this first example we define features “by hand”:

from dna_features_viewer import GraphicFeature, GraphicRecord
features=[
    GraphicFeature(start=0, end=20, strand=+1, color="#ffd700",
                   label="Small feature"),
    GraphicFeature(start=20, end=500, strand=+1, color="#ffcccc",
                   label="Gene 1 with a very long name"),
    GraphicFeature(start=400, end=700, strand=-1, color="#cffccc",
                   label="Gene 2"),
    GraphicFeature(start=600, end=900, strand=+1, color="#ccccff",
                   label="Gene 3")
]
record = GraphicRecord(sequence_length=1000, features=features)
record.plot(fig_width=5)

Reading the features from a GenBank file

DnaFeaturesViewer plays nice with BioPython. As a result it is super easy to plot the content of a GenBank file:

from dna_features_viewer import GraphicRecord
from Bio import SeqIO
with open("./plasmid.gb", "r") as f:
    record = SeqIO.read(f, "genbank")
graphic_record = GraphicRecord.from_biopython_record(record)
graphic_record.plot(fig_width=10)

Displaying the features along with other plots

As it uses Matplotlib, Dna Features Viewer can display the features on top of other sequences statistics, such as the local GC content:

import matplotlib.pyplot as plt
from dna_features_viewer import GraphicRecord
from Bio import SeqIO
import numpy as np

figure_width = 10
fig, (ax1, ax2) = plt.subplots(2,1, figsize=(figure_width,5), sharex=True)

# Parse the genbank file, plot annotations
with open("./plasmid.gb", "r") as f:
    record = SeqIO.read(f, "genbank")
graphic_record = GraphicRecord.from_biopython_record(record)
_, max_y = graphic_record.plot(ax=ax1m , with_ruler=False)

# Plot the local GC content
def plot_local_gc_content(record, window_size, ax):
    gc_content = lambda s: 1.0*len([c for c in s if c in "GC"]) / len(s)
    yy = [gc_content(record.seq[i:i+window_size])
          for i in range(len(record.seq)-window_size)]
    xx = np.arange(len(record.seq)-window_size)+25
    ax.fill_between(xx, yy, alpha=0.3)
plot_local_gc_content(record, window_size=50, ax=ax2)

# Resize the figure
fig.set_size_inches(figure_width, 2 + 0.4*(max_y+2))

Dna Features Viewer is pretty minimal in terms of features but easily extensible since it uses Matplotlib as a backend.

Bonus

As a bonus, here is what to expect when you feed it with a pathologically annotated Genbank file:

Release History

Release History

0.1.0

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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Download Files

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TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
dna_features_viewer-0.1.0-py2-none-any.whl (10.3 kB) Copy SHA256 Checksum SHA256 2.7 Wheel Sep 22, 2016
dna_features_viewer-0.1.0.tar.gz (12.2 kB) Copy SHA256 Checksum SHA256 Source Sep 22, 2016

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