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KAlignedoscope: An interactive visualization tool for aligned clustering results from population structure analyses
Avery Guo1,2, Sohini Ramachandran3,4, Xiran Liu3
1Division of Applied Mathematics, Brown University, Providence, RI, 02912, USA.
Abstract:
Visualization plays an important role in the interpretation of analyses applied to population-genetic data, particularly when multiple clustering results are generated from the same input data and aligned to provide a comprehensive view of inferred population structure. We present KAlignedoscope, a web-based tool for the interactive visualization and exploration of aligned clustering results. Built with D3.js, our tool enables fast, dynamic rendering and offers powerful interactive features such as reordering populations and clusters, sorting individuals, highlighting clusters, and customizing colors. The tool is compatible with outputs from clustering alignment methods Clumppling and Pong, and is easily extendable to others. KAlignedoscope supports and streamlines population structure analysis by enabling flexible navigation of complex patterns in the aligned clustering results.
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