Simultaneous visualization of cells and marker genes from scRNA-seq studies

Sengupta, D.; Gupta, K.; Ahuja, G.; Chakraborty, T.; Chakraborti, S.; Mittal, A.; Sinha, D.

doi:10.1101/2022.12.27.521966

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bioRxiv · 10.1101/2022.12.27.521966

Simultaneous visualization of cells and marker genes from scRNA-seq studies

Sengupta, D.·Gupta, K.·Ahuja, G.·Chakraborty, T.·Chakraborti, S.·Mittal, A.·Sinha, D.

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Abstract

The complexity of scRNA-sequencing datasets highlights the urgent need for enhanced clustering and visualization methods. Here, we propose Stardust, an iterative, force-directed graph layouting algorithm that enables the simultaneous embedding of cells and marker genes. Stardust, for the first time, allows a single-stop visualization of cells and marker genes on a single 2D map. While Stardust provides its own visualization pipeline, it can be plugged in with state-of-the-art methods such as Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (tSNE). We benchmarked Stardust against popular visualization and clustering tools on both scRNA-seq and spatial transcriptomics datasets. In all cases, Stardust performs competitively in identifying and visualizing cell types in an accurate and spatially coherent manner.

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Sengupta, D., Gupta, K., Ahuja, G., Chakraborty, T., Chakraborti, S., Mittal, A., Sinha, D.. 2022-12-27. Simultaneous visualization of cells and marker genes from scRNA-seq studies. https://doi.org/10.1101/2022.12.27.521966

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