The Tangram algorithm uses deep learning to align dissociated single-cell RNA-seq data onto spatial transcriptomics data, enabling genome-wide spatial mapping and imputation.
Datlinger et al. introduce CROP-seq, a method that captures both a CRISPR guide RNA and its resulting single-cell transcriptome, enabling causal gene function mapping at unprecedented scale.
This analysis elegantly demonstrates that the high number of zeros in droplet-based scRNA-seq is not a technical artifact but is well-explained by standard count statistics, implying "excess" zeros are biological.