Modeling zero inflation is not necessary for spatial transcriptomics

HIGHLIGHTS

SUMMARY

    Stereoscope and RCTD models count data with negative binomial (NB) and Poisson regression, respectively, to perform cell type decomposition. gimVI models count data with either NB or zero-inflated NB (ZINB) for missing gene_expression imputation. The authors present a comprehensive analysis on 20 spatial transcriptomics datasets collected from 11 distinct technologies to characterize the distributional properties of the gene_expression count data and understand the statistical property of the zero values. Specifically, for each data in turn, the authors carried out cross-gene analysis, gene-specific analysis, location-specific analysis and conditional analysis to characterize . . .

     

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