A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics.

ABSTRACT: Spatial transcriptomics technologies are used to profile transcriptomes while preserving spatial information, which enables high-resolution characterization of transcriptional patterns and reconstruction of tissue architecture. Due to the existence of low-resolution spots in recent spatial transcriptomics technologies, uncovering cellular heterogeneity is crucial for disentangling the spatial patterns of cell types, and many related methods have been proposed. Here, we benchmark 18 existing methods resolving a cellular deconvolution task with 50 real-world and simulated datasets by evaluating the accuracy, robustness, and usability of the methods. We compare these methods comprehensively using different metrics, resolutions, spatial transcriptomics technologies, spot numbers, and gene numb

SUBMITTER: Li H 

PROVIDER: S-EPMC10027878 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature