/divbrowse

A web application for interactive visualization and exploratory data analysis of variant call matrices

Primary LanguageSvelteMIT LicenseMIT


PyPI Docker Image Version (latest semver) GitHub release (latest SemVer)

Peer-reviewed paper in GigaScience Journal

Documentation Status Python PyPI Downloads Libraries.io dependency status for latest release License


Website: https://divbrowse.ipk-gatersleben.de
Documentation: https://divbrowse.readthedocs.io
Paper: https://doi.org/10.1093/gigascience/giad025


Table of contents:


About DivBrowse

DivBrowse is a web application for interactive exploration and analysis of very large SNP matrices.

It offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data. The use of standard file formats for data input supports interoperability and seamless deployment of application instances based on established bioinformatics pipelines. The possible integration into 3rd-party web applications supports interoperability and reusability.

The integrated ad-hoc calculation of variant summary statistics and principal component analysis enables the user to perform interactive analysis of population structure for single genetic features like genes, exons and promoter regions. Data interoperability is achieved by the possibility to export genomic diversity data for genomic regions of interest in standardized VCF files.

Installation

The installation via pip or container images is described in the documentation: https://divbrowse.readthedocs.io/en/stable/installation.html

Try out DivBrowse

If you want to test DivBrowse please visit the demo instances listed here: https://divbrowse.ipk-gatersleben.de/#demo-instances

Screenshots

DivBrowse GUI

Usage workflow concept

Usage workflow concept

Architecture

Architecture