Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method.

ABSTRACT: Integration of single-cell and spatial transcriptomes represents a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale data sets comprising millions of cells. Here, we introduce Polyomino, an intelligent region-allocation method inspired by the region-of-interest (ROI) concept from image processing. By using gradient descent, Polyomino allocates cells to structured spatial regions that match the most significant biological information, optimizing the integration of data and improving speed and accuracy. Polyomino excels in integrating data even in the presence of various sequencing artifacts, such as cell segmentation errors and imbalanced cell-type representations. Polyomino outperfor

SUBMITTER: Cai Q 

PROVIDER: S-EPMC12581947 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature