Bandage: interactive visualization of de novo genome assemblies.

Bioinformatics

Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne and.

Published: October 2015

AI Article Synopsis

  • - Bandage is a tool designed to help users visualize de novo assembly graphs, making it easier to understand the connections (edges) between assembled contigs (nodes).
  • - Users can interact with the graph by zooming in, moving nodes, adding labels, changing colors, and performing BLAST searches, with results highlighted directly in the graph.
  • - The software is open-source, compatible with Linux, OS X, and Windows, and can be accessed through its GitHub page, along with additional resources and contact information for support.

Article Abstract

Unlabelled: Although de novo assembly graphs contain assembled contigs (nodes), the connections between those contigs (edges) are difficult for users to access. Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone.

Availability And Implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage.

Contact: rrwick@gmail.com

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595904PMC
http://dx.doi.org/10.1093/bioinformatics/btv383DOI Listing

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