genomenotebook 0.4.1

A genome browser in your Jupyter notebook

Getting Started

Documentation

https://dbikard.github.io/genomenotebook/

Install

pip install genomenotebook

How to use

Create a simple genome browser with a search bar. The sequence appears when zooming in.

#Using the example E. coli genome data from the package
import genomenotebook as gn
import os
from bokeh.io import output_notebook
output_notebook() 

data_path = gn.get_example_data_dir()
genome_path = os.path.join(data_path, "MG1655_U00096.fasta")
gff_path = os.path.join(data_path, "MG1655_U00096.gff3")

g=gn.GenomeBrowser(genome_path=genome_path, gff_path=gff_path, init_pos=10000)
g.show()

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    <a href="https://bokeh.org" target="_blank" class="bk-notebook-logo"></a>
    <span id="p175635">Loading BokehJS ...</span>
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Adding a track with random points as a demonstration. genomeNotebook uses the Bokeh library and track.fig is a simple Bokeh figure on which you can plot anything you want using Bokeh.

import numpy as np

track = g.add_track()

x= np.arange(0,100000,100)
y= np.random.randint(0,10,size=x.shape)
track.fig.scatter(x=x,y=y)
g.show()

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Plotting some ChIP-seq data

Track objects also have a few custom plotting functions: line, scatter and bar.

A pandas DataFrame is passed as the source of the data as follow.

import pyBigWig
import pandas as pd

g=gn.GenomeBrowser(genome_path=genome_path, 
                   gff_path=gff_path, 
                   bounds=(0,100000), 
                   search=False, 
                   show_seq=False)

#Importing some coverage data from a BigWig file
bw_file_path=os.path.join(data_path,"ChIP-ACCCA-1.bw")
refname='NC_000913'
with pyBigWig.open(bw_file_path) as bw:
    cov=bw.values(refname,0,g.genome_size,numpy=True)
    
source=pd.DataFrame({"pos": np.arange(0,g.genome_size,10),
                     "cov": cov[::10]})

track=g.add_track()
track.line(source,pos="pos",y="cov")
g.show()

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Plotting some CRISPR screening data

#Opening the Cui 2018 CRISPRi screen data
cui2018data="https://gitlab.pasteur.fr/dbikard/badSeed_public/raw/master/screen_data.csv"
cui2018data=pd.read_csv(cui2018data,index_col=0)
cui2018data.head()

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	gene	essential	pos	ori	coding	fit18	fit75	ntargets	seq
guide
AAAAAACCTGCTGGTGAGGC	NaN	NaN	2202483	-	NaN	-4.850012	-1.437546	1	AAAGCAGATCACAGTAAATAAAAAAACCTGCTGGTGAGGCAGGTTC...
AAAAAACGTATTCGCTTGCA	curA	False	1517891	+	False	-0.094026	-0.100313	1	TGTTGATGGCTACAGTGCTGAAAAAACGTATTCGCTTGCAAGGTTT...
AAAAAAGCGCACTTTTTGAC	NaN	NaN	1919717	+	NaN	-1.109310	-0.246740	1	GTAACGCCTGACAGCGCACAAAAAAAGCGCACTTTTTGACTGGCAC...
AAAAAAGCGGTGACTTACGA	bglA	False	3042929	+	False	-1.328831	-0.905068	1	GCGCCCATATCGAAGAGATGAAAAAAGCGGTGACTTACGATGGCGT...
AAAAAATCTGCCCGTGTCGT	gyrA	True	2337231	-	False	-0.840373	-0.598858	1	ATGACTGGAACAAAGCCTATAAAAAATCTGCCCGTGTCGTTGGTGA...

g=gn.GenomeBrowser(genome_path=genome_path, 
                   gff_path=gff_path, 
                   bounds=(0,1000000), 
                   search=False, 
                   show_seq=False)

track=g.add_track(height=100)
track.scatter(source=cui2018data,pos="pos",y="fit75",factors="ori")

track2=g.add_track(height=100)
track2.scatter(source=cui2018data,pos="pos",y="fit18",factors="ori")
g.show()

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