Modeling temporal and spatial gene expression patterns in large-scale single-cell and spatial transcriptomics data is a computationally intensive task. We present PreTSA, a method that offers computational efficiency in modeling these patterns and is applicable to single-cell and spatial transcriptomics data comprising millions of cells. PreTSA consistently matches the results of state-of-the-art methods while significantly reducing computational time. PreTSA provides a unique solution for studying gene expression patterns in extremely large datasets.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10996487 | PMC |
http://dx.doi.org/10.1101/2024.03.20.585926 | DOI Listing |
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