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arXiv · 2512.18166

quollr: An R Package for Visualizing 2-D Models from Nonlinear Dimension Reductions in High-Dimensional Space

Jayani P. Gamage·Dianne Cook·Paul Harrison·Michael Lydeamore·Thiyanga S. Talagala
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Abstract

Nonlinear dimension reduction methods provide a low-dimensional representation of high-dimensional data by applying a Nonlinear transformation. However, the complexity of the transformations and data structures can create wildly different representations depending on the method and hyper-parameter choices. It is difficult to determine whether any of these representations are accurate, which one is the best, or whether they have missed important structures. The R package quollr has been developed as a new visual tool to determine which method and which hyper-parameter choices provide the most accurate representation of high-dimensional data. The scurve data from the package is used to illustrate the algorithm. Single-cell RNA sequencing (scRNA-seq) data from mouse limb muscles are used to demonstrate the usability of the package.

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Jayani P. Gamage, Dianne Cook, Paul Harrison, Michael Lydeamore, Thiyanga S. Talagala. 2025-12-20. quollr: An R Package for Visualizing 2-D Models from Nonlinear Dimension Reductions in High-Dimensional Space. https://arxiv.org/abs/2512.18166

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