PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.

bioRxiv

Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.

Published: March 2024

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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10996487PMC
http://dx.doi.org/10.1101/2024.03.20.585926DOI Listing

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