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bioRxiv · 10.64898/2025.12.12.694028

Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI

Danning, R.·Ke, Z. T.·Lin, X.·Ma, R.
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Abstract

The prioritization of highly-variable genes is an important step in single-cell trajectory inference. However, when variability arises from a continuous latent cell development trajectory, standard methods may fail to differentiate trajectory-relevant from uninformative genes. SEEK-VFI is an ensemble topic-modeling machine learning algorithm for trajectory inference preprocessing that prioritizes trajectory-relevant genes. It outperforms existing methods, and identifies key genes that improve trajectory topology reconstruction, enhance visualization, and augment downstream trajectory analyses.

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Danning, R., Ke, Z. T., Lin, X., Ma, R.. 2025-12-16. Trajectory-informed gene feature selection in single-cell analysis with SEEK-VFI. https://doi.org/10.64898/2025.12.12.694028

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