2026/03/27 by Avery Guo, Sohini Ramachandran, Xiran Liu · 1 voice
Computer Science · Decision Sciences · #Data Visualization and Analytics #Scientific Computing and Data Management #Data Analysis with R
paper · pdf · doi:10.47248/hpgg2606020006
openalex publication_date 2026/03/27 · openalex created_date 2026/03/28 · openalex updated_date 2026/07/31
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.