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Interactive heatmap for multi-sample structural variant analysis

Project description

VariantMap - Interactive heatmap for multi-sample structural variant analysis

Build Status PyPI pyversions PyPI versions Conda Github release PyPI license


VariantMap is a genomic structural variant (SV) visualization technique that displays variants across multiple samples in an interactive heatmap. It is a browser-based app implemented through Dash by Plotly. Each row of the heatmap represents an input sample and each column represents an SV breakend found in the sample cohort. The colors indicate the class of an SV present in a sample. More details of each variant can be displayed by simply hovering over them . The heatmap can be customized to suit your analysis by changing various components in the "Customize" tab.

VariantMap requires a dataframe object (HDF5 file) that can be generated by VariantBreak which in turn requires VCF files generated by NanoVar which calls SVs using third -generation long-read sequencing data. Future upgrades will enable VariantBreak to use VCF files produced by other tools.

Basic capabilities

  • Visualize the prevalence of variants and their classes across sample cohort
  • User-friendly interface to analyze and customize your data without the use of programming language
  • Obtain the variant size, score, read coverage, and genotype by simply hovering over them
  • Easy filtering of variants by gene name, gene type, gene feature, repetitive elements, or other annotations, depending on input annotation files
  • Capture snapshots of heatmap by just one click
  • Convenient uploading of datasets directly from the app interface

Getting Started

Launch the app and upload your HDF5 (.h5) dataset

# This Python script is installed in your PATH, execute it from anywhere 

Operating system:

  • Linux (x86_64 architecture, tested in Ubuntu 16.04)


There are three ways to install VariantMap:

Option 1: Conda

# Installing from bioconda
conda install -c bioconda variantmap

Option 2: Pip

# Installing from PyPI
pip install variantmap

Option 3: GitHub

# Installing from GitHub
git clone 
cd variantmap
pip install .

Installation of dependencies

These should be automatically installed, or else, you have to install them manually:

  • pandas >=1.1.4
  • dash >=1.17.0
  • tables >=3.6.1
1. pandas
pip install pandas

or Please visit here for instructions to install.

2. dash
pip install dash

or Please visit here for instructions to install.

3. tables
pip install tables


conda install -c conda-forge pytables


See wiki for more information.




Not available



VariantMap is licensed under GNU General Public License - see LICENSE.txt for details.


  • VariantMap is only compatible with HDF5 datasets produced by VariantBreak

  • VariantMap may not be able to handle large HDF5 files (>32M) in Google Chrome. Do try with Mozilla Firefox for these larger files.

Project details

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Source Distribution

variantmap-1.0.2.tar.gz (4.0 MB view hashes)

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