SD2: spatially resolved transcriptomics deconvolution through integration of dropout and spatial information.

ABSTRACT:

Motivation

Unveiling the heterogeneity in the tissues is crucial to explore cell-cell interactions and cellular targets of human diseases. Spatial transcriptomics (ST) supplies spatial gene expression profile which has revolutionized our biological understanding, but variations in cell-type proportions of each spot with dozens of cells would confound downstream analysis. Therefore, deconvolution of ST has been an indispensable step and a technical challenge toward the higher-resolution panorama of tissues.

Results

Here, we propose a novel ST deconvolution method called SD2 integrating spatial information of ST data and embracing an important characteristic, dropout, which is traditionally considered as an obstruction in single-cell RNA sequencing data (scRNA-seq) analysis. F

SUBMITTER: Li H 

PROVIDER: S-EPMC9789790 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature