Geneview: A python package for genomics data visualization

Geneview is a Python visualization library base on matplotlib. It provides a high-level interface for drawing attractive genomics graphics. And now it is actively developed.

Documentation

Examples

We use a dataset GOYA_preview which is in geneview-data repository, as the input for the plots below. Here is the format preview of GOYA_preview:

A basic example for Manhattan plot.

import matplotlib.pyplot as plt
import geneview as gv

df = gv.util.load_dataset('GOYA_preview')  # df is DataFrame of pandas
xtick = ['chr'+c for c in map(str, range(1, 15) + ['16', '18', '20', '22'])]
gv.gwas.manhattanplot(df[['chrID','position','pvalue']],  
                         xlabel="Chromosome", 
                         ylabel="-Log10(P-value)", 
                         xticklabel_kws={'rotation': 'vertical'},
                         xtick_label_set = set(xtick))
plt.show()

A basic example for QQ plot.

import matplotlib.pyplot as plt
import geneview as gv

df = gv.util.load_dataset('GOYA_preview')  # df is DataFrame of pandas
gv.gwas.qqplot(df['pvalue'], color="#00bb33",
               xlabel="Expected p-value(-log10)",
               ylabel="Observed p-value(-log10)")
plt.show()

Citing

Dependencies

• Python 2.7 or Python 3.4+

Mandatory

• numpy

• scipy

• pandas

• matplotlib

Recommended

• statsmodels

We need the data structures: DataFrame and Series in pandas. It's easy and worth to learn, click here to see more detail tutorial for these two data type.

Installation

To install the released version, just do

pip install seaborn

You may instead want to use the development version from Github, by running

pip install git+git://github.com/ShujiaHuang/geneview.git#egg=geneview

Testing

Development

License

Released under a BSD (3-clause) license