What is GenomeView?

GenomeView visualizes genomic data straight from python. Features include:

  • Easily extensible

  • Integrates with jupyter notebook / jupyterlab

  • High-quality vector output to standard SVG format

  • Includes built-in tracks to visualize:

    • BAMs (short and long reads)

      • Both single-ended and paired-ended views available
      • Includes a cython-optimized quick consensus module to visualize error-prone long-read data
      • Group BAM reads by tag or other features using python callbacks
    • Graphical data such as coverage tracks, wiggle files, etc

The output is suitable for static visualization in screen or print formats. GenomeView is not designed to produce interactive visualizations, although the python interface, through jupyter, provides an easy interface to quickly create new visualizations.


GenomeView requires python 3.3 or greater. The following shell command should typically suffice for installing the latest release:

pip install genomeview

Or to install the bleeding edge from github:

pip install -U git+https://github.com/nspies/genomeview.git

To display bigWig graphical tracks, the pyBigWig python package must also be installed, eg pip install pyBigWig.

Quick Start


To produce the visualization above, a single line of code suffices (in addition to information about the locations of the data and coordinates to be visualized):

dataset_paths = ["/path/to/pacbio_single_end_dataset.bam",
reference = "/path/to/reference.fa"

chrom = "chr1"
start = 224368899
end =   224398899

doc = genomeview.visualize_data(dataset_paths, chrom, start, end, reference)

If you are using jupyter notebook or jupyterlab, documents can be displayed simply by placing the name of the document on the last line of a cell by itself and running the cell.

To render the document to file, use the simple genomeview.save() command:

genomeview.save(doc, "/path/to/output.svg")   # or .png/.pdf

For more details on setting up your own document with fine-grained control over how the tracks are created and visualized, see the next section.